{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Kats 201 - Forecasting with Kats\n",
    "\n",
    "\n",
    "This tutorial will introduce time series modeling and forecasting with Kats. We will show you how to build forecasts with different Kats models and how to do parameter tuning and backtesting using Kats.  The complete table of contents for Kats 201 is as follows:\n",
    "\n",
    "1. Forecasting with Kats Base Models     \n",
    "    1.1 SARIMA     \n",
    "    1.2 Prophet     \n",
    "    1.3 Holt-Winters     \n",
    "2. Forecasting with Kats Ensemble Model\n",
    "3. Multivariate Model Forecasting\n",
    "4. Hyperparameter Tuning\n",
    "5. Backtesting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note:** We provide two types of tutorial notebooks\n",
    "- **Kats 101**, basic data structure and functionalities in Kats \n",
    "- **Kats 20x**, advanced topics, including advanced forecasting techniques, advanced detection algorithms, `TsFeatures`, meta-learning, etc. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. Forecasting with Kats Base Models\n",
    "\n",
    "\n",
    "\n",
    "In this part, we will demonstrate the forecasting workflow with the following models with `air_passengers` data set:\n",
    "1. SARIMA\n",
    "2. Prophet,\n",
    "3. Holt-Winters\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We begin by loading the `air_passengers` data set into a `TimeSeriesData` object.  This code is essentially the same as the code in our introduction to the `TimeSeriesData` object in the Kats 101 Tutorial."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "# For Google Colab:\n",
    "!pip install kats\n",
    "!wget https://raw.githubusercontent.com/facebookresearch/Kats/main/kats/data/air_passengers.csv\n",
    "!wget https://raw.githubusercontent.com/facebookresearch/Kats/main/kats/data/multi_ts.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import sys\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "\n",
    "warnings.simplefilter(action='ignore')\n",
    "sys.path.append(\"../\")\n",
    "\n",
    "from kats.consts import TimeSeriesData\n",
    "\n",
    "try: # If running on Jupyter\n",
    "    air_passengers_df = pd.read_csv(\"../kats/data/air_passengers.csv\")\n",
    "except FileNotFoundError: # If running on colab\n",
    "    air_passengers_df = pd.read_csv(\"air_passengers.csv\")\n",
    "\n",
    "# Note: If the column holding the time values is not called time, you will want to specify the name of this column.\n",
    "air_passengers_df.columns = [\"time\", \"value\"]\n",
    "air_passengers_ts = TimeSeriesData(air_passengers_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because each of our time series models follow the `sklearn` model API pattern, the code for each of the next three examples is quite similar.  We initialize the model with its parameters and then call the `fit` and `predict` methods.  The only difference between each of these examples are the model-specific parameters.  We can then use the `plot` method to visualize our forecast in each case.\n",
    "\n",
    "The values we choose for each of our paremeters in these examples are basically arbitrary.  Later in this tutorial, we will show you how to pick the right parameters for a model in Kats using hyperparameter tuning."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.1 SARIMA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='time', ylabel='y'>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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e/KmEEEIIIVrIWzbrW6drWss3090M1wtWZDOXKh6ZpMUH7h0mCBV//r2pVV9j6BqOF2x7NMS7Ybxjr5ECWQghhBBiA54XrZleztA1vBYdeNsK2wkaEW8QjVhkUhaDvSlOH+nmqy9M4a9RCG/3oF70wmBvHtADKZCFEEIIITbk+qsLZF3XWhaZthW2GzQi3iAascgkLQB+8L4RCmWPF87Mr/o6DQ3X317nu1VZyrcqKZCFEEIIITbgNSmQDV3b1ULRdq93kMNQUan6ZFImAKeOdNOVjfHK+cVVX6frUHW2VyCXbX9F93qvkQJZCCGEEGIdSin8QHFj5K+ua3jb7MRu55psN2jMRVdsHwWkax1kXdPo6Ug0spGXi5IsNh/1tlhwVq2nrkqBLIQQQgjx5hWGClBo2uoRi92aQfaDaPV1/ZpKtYI3k7Iaj8mmLEpNIt1Mc/NRb34QcnWyQPmG5IuK7e/ZiDeQAlkIIYQQYl1BqNCaHEjTNY1AqVoBvbN8f2UGcrESFcjZZQVyOmVSqqzuFJuGhu36m7ruiu1TKHsUik7jY0GocP2V8897zd79yYQQQgghWiAI1KoRgwal7UoWsheELN99Xa4VwvVDevX/v1TxVl27pmlobG5+ulzxiFs6czn7+vf293aCBUiBLIQQQohb0G4u4LhRECrGZ0v84q9/m7ml6spPahCEOz9mEXWQrxep9RGL9A0jFkEYzSo3s5kM58WCQyZl4bghVcevfV24x8tjKZCFEEIIcYup2j4XruV2+zIagjBkar5Krug2WeGsCIKdL+ajA3rX/3ex0UE2Gx+rH9hrNmahiDbhrccPQsrVaNZY06BYjg78uV6A2stbQpACWQghhBC3mIm5EoXy5lMW2i0IaRxq++bLMys7smp3ut1Vx8fUr5dx5YpP3NKJWUbjY/UDe80O5FmGTmWDg3pV20fVDicm4wZzS9GYRaW68nvvRXv7pxNCCCHEbaVc9VjIOahdKjybCYKAai3FoeoEPPfq7PVParVEiR1mOwGGsXLEYvl4BVzvJhebHtTTKTvrF8iliteIkYtZBuWqh+sFUXG+hxMsQApkIYQQQtxCJubKxCw9mu1dY03yTnO9kIrt052NsX8ow1e+O9k4+KahEQQ7n4UcLQlZuUUvm7yhQE6tPWJhGhrOBstClooOidj1jjS1MYvyHo94AymQhRBCCHGLKFU9lvJOY3b2Vukge15I2fbIpCw+cO8wU/MVzl/LA9FWOneHs5CDMJp7Xr7Zr1xp0kFujFisLpANQ8f1gzWj3oIgpFRZWQjHLYPZJRvfV43O8l4lBbIQQgghbgmTM2XijY7l7uQLN+P6UQc5k7S471Q/6aTJl2uH9XRt55eFeH7ADTtLKFW9FRFvAImYgaFrTUcsAFDRQbxmKsvmj5c/X7HsRV+4x0mBLIQQQohdV6p4LBUdUoloblZjd/KFm/H8KM0hnbSIWQbvu3uIl84tsJi3MXQNdxN5wq3k+2pVikSp6q9YEgJR3nEmZTUi4FbRWPPal88fL3++vZ5eUScFshBCCCF2Xb7kYJrXCzK1S/FpzUQFskcmFRXv73/7MAB//r3paN30DhfIN34/zw9x3IB0ylz12EzKolxZ4zCe0qI85SaWiu7K+eOadMIkEV/9ffYaKZCFEEIIses8L0S/YW4gXGt73Q5zvICqEzRmo3s7E+zrTzM+W8bYhQI5V3Swlh3QKzXZoleXSZprjlhoWn0r3krR/LHX9CBezDKaFs57jRTIQgghhNh1rh+ueEtf17QdP/zWTBCqxiG3zLIRhkzKolz1og7yDqZthKFiseCQXNbFrY9Q3DhiUb/OtUYsTEOjaq8ukKtOANrK+eM3GymQhRBCCLGrgiDg+e98G13XUErx2//3Wb7+vWn8Jt3Nnb+2sLFoY3mHNpO0KFX8aC433LlIuorjEwThigSLegf5xhSL+nWW1+ggG4beWB+9XLOPvdlIgSyEEEKIXfX5z3+ev/aTH+LP/+xPOXMlx7dfneXctfyOdmbXEoSKSm1JSCa1fI2zeT0+Tdu5SLpiyV1RHMMGIxYpi4rtN70+09BWbgWsKVe8FSMcb0Zv7p9eCCGEELtuYmICgN/57f/IH/3ZVSCKGdvp+LRmwmUjFunkyhGLiu1HUXRq5w4Uzi7ZK8YrYIMRi6SFYo0sZF3D8cLG0pO6Vi8CufH5bwd7/xiiEEIIIW5ps3NzAJwdK5OYKhKPGVRtH+8WSLEIQkWlyYhFOmmiiAr5neog266P7fp0Z+MrPl6qeGjQiMhbbvmykI50bMXnNE0DFaVgxKzo4J1Siorj09Gk2N6q33jqDMWKy32nBlr2nO0mHWQhhBBC7Kq5uTni8SRH3/FT6GGJd9zZT9n214wg20lBEBWMEBXFdfViOereagRh+6+1VPFWLQiJPu6TSpqrRi/g+lhIaY2oNw3wl70Q8fyQMGztAb2ZxSqGfnuVnLfX1QohhBBiz5mfm+fQXQ+Q6T3MmT//LSzdp2r7OLfCIb1QUa76xC290WWF6+MWpYoHih0ZsVjIO8St1RFrzbbo1dU/vlbUm7oh6s1xAzRaVxwrpZhfqtLTGd/4wbcQKZCFEEIIsavm5hcZOPUgPVmD8TPPcva1F1CAbQe7vk3P8wIqtr8qIeL66IJfyxNubwc5CEIKpebLO0oVb0UEXfPrXGObHmpFnJ7jBbSwPqZY8XC8UApkIYQQQoibkfeyWKkBfuKHjvPe972f5775LBDN9+5UfNpaXD+kYvurOrSZ2rhFqertyLrpUm0OutnoQ6m6doG8otPdhKnrK5IsKlUfs8moxlbNL9kA9HRIgSyEEEIIsWkVNypHjox28PDf+rsszIxFH3f8Xd+m59UK5OXzx3C98GwsC2nzOEiu6KxYpLJcqbL2iIVl6iRixrrLQhzn+rWXqj4xq3Xl4XwuKpB7OxMte86d0NYCOZfL8ZGPfIQ77riDU6dO8c1vfpPFxUUeeOABjh8/zgMPPMDS0lLj8Z/85Cc5duwYJ0+e5Atf+EI7L00IIYQQtwjHj8qRTNLk/R94gI5MVEzZVX/H4tPW4gXNO8gxS8cydUoVPyqQ2xxJt1R0SMRXj1copShV/TU7yBAtEFmrg2wYeuMQolKKqu1htjDibS5XBaBbOsjX/ezP/iwf+tCHOHPmDC+99BKnTp3iscce4/777+f8+fPcf//9PPbYYwC8/vrrPPnkk7z22ms888wzfOITnyAIdn84XwghhBDtY9s2So+jERCzDHRdp6+nE4CKW8sZ3kWeF1JuMsKgaRrppLkjIxaeH+K6AWaT5R1VJyAM1YolJjfK1rb+NWMaGo4XoJTC80OCMFrz3SrzOZuubKyluco7oW1XWygU+OpXv8rHP/5xAGKxGF1dXTz99NM8/PDDADz88MM89dRTADz99NN89KMfJR6Pc/jwYY4dO8Zzzz3XrssTQgghxC1gYWGBWKIDS79eYGbTUbdxrQ1wO8l2fKpO0HxLXdKiXCuQ23lIz3HXPji33ha9ukzKXHPEIspCVviBqhX5rb3fc0s2/V2313gFtHFRyKVLl+jv7+dv/s2/yUsvvcS9997Lr/7qrzIzM8Pw8DAAw8PDzM7OAtEWnXe/+92Nrx8dHW1s1lnu8ccf5/HHHwdgenqaycnJdv0It7W5Wui62B65j60h97E15D62htzH1mjVfXzjjTewEh3EzJDF+RkAYha4wOJSnqmpKSrF2PpP0iZhqJiYnAdAC6uN66uLm4pcoUJucZZi1Wdiwr3p/ODN3MelokN+qUxory6CJ2eiEQbll1ddX52lBxRK9pqfL1Y8xsddHDeIvo/TuvJwdrHM8dE0+aU5pqb8luYrL9fqv9dtK5B93+eFF17g137t13jXu97Fz/7szzbGKZpptoaw2U185JFHeOSRRwC47777GBkZad1F7zFyb1pD7mNryH1sDbmPrSH3sTVacR/PnDmDFc+STcXo6RsEoLtngAm3gtKH6O4dYKg3te3vsxW262NeijqvA/09pDt60HWtMS7Q1bnI+EyZnr5B9JLD4FB/0zGIjWx0Hytjefr7s0035Y0vLQAwPNhPT1+26df3dpd57UqpcX9vpBcdevu7yZdceoP0uvPMN8P1AoqVc+wb6qazu5/h4YGmy0xapZV/r9s2YjE6Osro6Cjvete7APjIRz7CCy+8wODgIFNTUwBMTU0xMDDQePzY2Fjj68fHx+U/YEIIIcQeNz8/j5XoIJuJxipsx6e/rxfPKVIq223PF16P76tGfnA6aVF1g0bcWv1jjdGFNi4LKVU84mskS9S//3pFbSZl4XohrrfG2a5ajnOl2toDevUEi77bcMSibQXy0NAQ+/fv5+zZswA8++yz3HnnnTz44IM88cQTADzxxBN8+MMfBuDBBx/kySefxHEcLl++zPnz53nnO9/ZrssTQgghxC2gXiB3d0Rd4qobcPjgML5dolh22h6ftp56xBvUC1CFpqlG9FwmaVKp1g8Sam2Zl/b8EM8PMNboTNcP362bYrFBFrKha9iOH0W8taFAlhnkG/zar/0af+2v/TVc1+XIkSP81m/9FmEY8tBDD/GZz3yGAwcO8LnPfQ6A06dP89BDD3HnnXdimiaf/vSnMYzVcSZCCCGE2DtmZuawEvvp6cpQtX06UhYjQ/14zllKFRff371Dem5tix7UFoMoyKQtqrZPOmmRTlooosOEmkZblprYjs96dXep4mEa2podZqCRcFGq+tQCQlYwdZ1ixSMMw5aOQMzVloT0dSd2/bDlzWprgXzPPffw/PPPr/r4s88+2/Txjz76KI8++mg7L0kIIYQQt5Dp+QIAHZk4thtwZLSDyd5oxKLq+Ls6YmG7AdXaEo100qJs+/R3Jbk8UQSud21LVY9E3MBrw4hF1fHXLVrrW/TWO/yWTW2wTc/Uqdo+qNbOB8/nbBIxg0zSIl92W/rc7XZ7hdIJIYQQYk+ZXywB0ca3rmycbDpGT08Pnl3CcdXuFsiOT8X2ScSM6GCegq5sHMPQouzhxjY9H13TcJzmWcPbUSh7xNY5+FeqrL1muq4xYrFG1JthaPiBQmmtLfDnc1X6uhJtS65oJymQhRBCCLFrcoXobfi4ZTDQkwSgp6cH3yniBu1f4bwe2w1q4xQmSil0PSrk+7oSK9ZPl6oelqlTtltfIBfL7rqrnxfzNt3Z9bfUZTaYQdY1DT8I11xlvVVzSzZ93bff/DFIgSyEEEKIXVSoFW2phIlpRAVab28vnlMCNKpusCvb9JRSON71NdNhqBrxbr2dCbwgvN5BrniYht6YV24V1wvw/HDNA3pKKeZz9oYpEamkiaatXSADBKHCMlt39itUioW8TX9XsmXPuZOkQBZCCCHErqk40QhFOmU2CsF0Oo3yKwBU7WBXDnh5fggq6g6nU9aKAjKVMDFNnWQ8+t+lqo9pREkQrSzmHTdgzRV6RNfmeOGGBbKuaSsj6Zro60qQiLWuQM4VXfxA3ZYRbyAFshBCCCF2kRNEpUgqbjbe4tc0jXhtrDZaN73zc8h+oECLit96B7kegabrGoM9SbwgxDQ0ylWvMWfbypnpquOjrVOpzS9tPmc4kzTX7SDrLZ4Tns9FG/76ZcRCCCGEELc6pRTVNhwm24pKpYKmJ9AIsCwdw7hepKUSUYlSrfrsQn1c6yAryhWPTMqMOsjLZoG7s3FCtXJZiKK1BfJGB/Tm8zdRIKesFUtO2u1mivdbkRTIQgghxJtIueozPlPa7csAYGFhASvRQcwIAW3FIbGOVHTwrOL4bckX3ogfhPhhiO0GZJLRiMXyJRqJeDTXm0lZlGvLOjS0tbfVbUGh7BJbZ+yhvoijt3OTBfI6HeRWm8vZ6Br0dKx/gPBWJQWyEEII8SZSLLuUd7CTuJ76Fr2EpWEa2oo4sK5aMkM0YrHzM8i242Mvy0AOQ4VlXS9WDV2LZnsTZqODbBi0rDvvegG+r9ZNlljIOXSkLeKbmB3OJHe2QJ5fsunuTKx5wPBWd3tetRBCCCG2ZD5v4/khSu3+ZrN6gZxKmo2EiLre7jQQFZy7kWJRdYLaIbnaJjqNVcWqaeikkyblWoFsGXrLXnzUv/d65nPVTXWPodbprnqNNdntNper3pYrpuukQBZCCCHeJFwvyvVVil0pOm9UL5CzqdiK8QWA3p4uAs+mYu/ONj3HDbDrBXLSQkNbMSMNUSZyKnH98Jtlti7qbTM/83ze2fSMbyZpESqijXk7YD5n37YH9EAKZCGEEOJNo2L7KDTQ2JWxhRvNzc1hJbJ0dqQwbyiQ+/r68Owi5YqDtwszyNGSkNqIRcoCFXWMl6sXyGXbJ1QKw9Bx/dbE0pVtv5EL3UwQKpbyNr2bLJA70lEsSK7U/pXPVdunXPVv2wN6IAWyEEII8aaRKzjETA2UuiUK5JnZBax4hs5salUHuaenB88pUizb+N7OFshBEBIEirIddYYzSavpiEXM1EklLNTyzqxqzfa/6gYF8lLBIVSsGmNwvQC/yQuK/u5oYUc9XaKdJubKK77n7UgKZCGEEOJNQCnFQtEhETdvmQ7yzHwegEwqtuIAHNTXTZcoVVzcHR6x8IIQTaORThGtlFarRywsnWSitiykNmahaeC2oKCv2P6quezl6jnDN3ZpK07QdCFIfdxhbqm67WvbyLdfnSVm6dxxqKvt36tdpEAWQggh3gRsJyDww1oXVCMIdr9AXliKOo3JhLFmB7li+9HSjh3k+wqFolT1SMQNTENH3RBDBxCzdJJxE6BxOE+hth31FoQK1w/WTYCYzzkATUYsFBqsOoSZTlqkkyazbS6QbTfgO6/Pce8d/Y17czuSAlkIIYR4EyhVPRzX4ac/9iB/8vR/vyU6yEuF6O3+dMJa1Z3t7e3Fc0rYnmrJyMLNqB+QK1e9xha9G2PoAAz9eoFc79qauk5lm0kW0c+7/ma7+ZyNrmt0Z2/MGdaIx0ycJl3s/u4ks20esXjhjTkcN+B99wy29fu0mxTIQgghxJvAYsHhd37jV/nOc9/mhe98gyDY2aKzmfpmt1TCWrXquKenB98u4vkaXguXb2yG6wVoaOTLHtlUtCSk2biDYWi18YvrHWTL1Ledhex64QblMSzkbHo74ug35iQrGOhOYLurr2GgO9H2EYuvvzTNUG+SI/s62vp92k0KZCGEEGKPC4KQF198id/6jV/nXQ99mpJxpCVzsttVcaJrSCfNVeME0YhFCYVG1Q12NJbOdgNMQ4uK0M4E4Q1b9OoMXW8UyI0OsqlT3maUmusFKNb/eedzdvOUCE3R1REHtbrE7u9OspR32habNzlX5tJEkffdPbSq2367kQJZCCGE2ONKFZd//k/+PwwcuItkxyAeKbxdLpCVUrh+VIakEsaq+d5MJkPoVYBoq91OjoTYjo+uaSwWHHq7ElEH2WpWIGvEreja64f0DF3D99Wm12MvFZ1VxX+l6mPq65do87nqqvnjMFQYuk4iZpJJmauWjQx0J1FcX1Hdat94aQZD13jnWwba8vw7SQpkIYQQYo/79Kf/Pa++/F1+9KP/AIAAa8eTIW5ULpfRrBQ6Aaapr5pB1jSNuBUVjhV75zvI5apHGCp6O+PRmmlz9Trn+jVHW+qWd43Vpjr0fhAys1BZtVyk6qyfYGE7PqUmOcPLR0H6upKNRSd17Uyy8PyQb706w90neulIx1r+/DtNCmQhhBBiD5uYmOBf/PN/wrvf9wFIjAKgtNiubKdbrr5FzzJCaJIQAVFnGaLIs53qICulcLyQxUKUEtFX6yA3G7HQ9WjpSjpprohWU7CpFyAV26dS9SmUnBUfL9v+qsUpy83nr1/bcmGoiNU63Z2ZGDdula7nErcjyeLl8wuUqz7vu3uo5c+9G6RAFkIIIfaw3//936dcKvHz/8cnuTRZBEA3k9uOItuu+fl5rHiWRExrmhABkE1F298qtr9jHWTPD0HRKJB7OxMoRfNDerXIvEzSaoxYAOiahuttPIdcrnhYpt4oeCGaF/d91fQFQ91CbURivQI5HjNIJYwVf86ZlEUqYTK32PoRixfPztOZid3W2cfLSYEshBBC7GETE5NYVgzf6CMMFUmjipnoIF8s7up11TvI6YS55jhBVyaKMKvaAUG4Mx1vP1CgwULeRgO6O+LRFr0mmcSaFhX36aRJeVkH2TQ0KvbGL0CWig6phEnV8RvzwtFoxsYH9GB1gRzcMAoy0JOk4qwes2j1iIVSirNX89xxqGt1qsZtSgpkIYQQYg+bmp6mu6ePNy7niFs6g1kXK55haWFhV7OQ5+fniSU66EjHm44vAPR0pwCoON6OLQuJOsiKhZxDZzZWK95Xb9Grs0ydVMJsRNYBmIZOZYOotyAIKVWiUQpNiw5SwuZGM+ZzNom4QSqxchFHECriyw4TZtMxbpyziLKQW1sgT85XKFU8Th7saunz7iYpkIUQQog9bHZmlu7eqEA+fqCLrtpiidn53KaTFtpyXXNzWIkOOjtSTRMiAPp7uwl9F9sJcN2dGQkpVlx0XWMhH0W8AaBYc+TBNHVSCYtK1SOsFaOmoeE4619vxfZBi7bexU2DxdqYhev5aBt0YesRbzeOpSgF5rIOcswyVu0bGehOslhobdTb2Ss5AE4c7GzZc+42KZCFEEKIPWxmZoa+oaPMLlU5dbiL7s7ooNbCYn5XO8jTM/OY8XRUIDdJiID6Nr0ipYqzKrKsHZRSzC/ZpBIm83mb3s7aljqt+SFCAMvQSSUMQgXVWhqFYei43vrJG6Wqj1arXuNxg1zJJQgVFTvA3KBAXsjb9HU2yUBm5eyyoWvomtYo3CFaFqJU9Bytcu5qnr6uxPUXFHuAFMhCCCHEHjY7O0t28DQAdx7pprc72nC2mCvuaoE8O18AIJ201h6x6OnBs4sUSjbODqybrtg+jhegaRq5gtMo+DSazyADxGodZIDisoN6aBr+Oh36paJDIha9MKgXsZWqR7m6fsSbUmqdJSFR93o5y9RXFOr1JIu5xdaMWYSh4txYfk91j0EKZCGEEGLPUkoxPz+HmT1ET0ecwZ4k/T1RIVMoVgh2aK63mfmlEgDJdQ7p1bfplSrOjmz+K5Si8YpcwSFU0NuVQCmFpq09YmFZBl0dUe7v/NL1rqymWHNuOggVpYrbSJyAqLDNl12qjo+5RjEOUCh7eH64aklI7buumpW2TGNFgTzQU496a00HeWymRNX299T8MUiBLIQQQuxZuVwO3/dx9F5OHe5G0zQGBroBKFRWb3DbSXOLZQDScWvNA3C9vb34TpGKHbS9QFZKMbtUJRWPxiuAZUtC1i6XYpYeJV2wMl9Yodac863WDvAtnyFOxEzmlqoEQbhuEsSFsTwAI32pVZ/TiDbprbi+GzrI6aRJMm60LMni3LXoeqRAFkIIIcRtYXxiiuzAcQJlcOpwFwCJeFTMVar+uiMA7ZYrRgVaKmGuKurq6iMWthsShGFbR0JsJ8BxQyxTb8zn9nYmVkWn3UjXNDJJk3jMWLnCWWPN+1uueKsO2FmmHq3/bpIHvdw3Xp6huyPOsf2rRxpUk8OEpqGtuG+aptHfnWSuRR3ks1dyDPUm6czc/tvzlpMCWQghhNijJqam6Rw8BSzr8GkQBi62G+Lv0ja9IAio2NH3TqXMNccX6iMW0a4Lra2pG7mSi1arihZyDpoWZSCvtUWvzjA0dE2nvyuxoug0dA17jai3XNEhbjUrurV1I5AXCw5vXFriPXcNruoyh6HCMPVVH7csfcUhPYiSLFoR9RYEIRfG8pzYY91jkAJZCCGE2LOmJqdJd42SimtkalvplILQr+L6m8vcbYfJySmMWBqAVNxYc8Sip6cH3ykSKh3PD9uahTyfq5KsHZpbyNt0ZeOYRjSesFYMHdQ6tgr6bljAYeo61SZRb0GoKJS9FfPHdR1pi2zKXPXxum+9MoMC3vPWwabP26yQj1k6N+5Y6e9OsJC3t/0OwtWpEo4XcnKPHdADKZCFEEKIPWtyaopU1z76awe6PD8kETPQQgc/NKO39HfB5StXsRIdWIbCNPU1O8jZbJbAqwBRhFq7OshVx6dq+1FuMPUYtWgUZTMdZLSoK7uQtxvzvoahNc1uth0fpaLRjBvpurZmWkaoFN94eYaTBzubJlisdZ2GYaBuaEv3dydRikb28ladvZoD4MSBrm09z61ICmQhhBBij5qamiHVuY+RgSwAtuvT05nA1HxCzdq1DvK1a2PEEh0k4wagrXkoTdM04mZU3JWqbts6yIWSu2L2dyHv0FOLeAuVwmo6DhExdB2lorXPfqDIFaOi0zR0bG91gbzVPOfz1/Is5Gze+9ahpp9fq9Nd73Av10iy2GbU29mrOfYNpBvvTuwlUiALIYQQe9Tk7CKxVBdDfdE4QxBAZyZG3FRoRhJvB7KFm7l2bYxYuofObBzT0FYdWFsuGYuK+FLZxw/ac70LeacxXuEH4YoMZFidLbycoWugKfq7o8fX49N0PcpBvvFgYanirft8a/nGSzMk4wb3nOxt+vkwVI0O+Irrq3W4l7t+rVsvkP0g5NJEkRMH9t54BUiBLIQQQuxJYahYyEeLKwZ7kqjaQa10wiQZ1zBiaRy3+SGydrt67RqpzhGGejPrRqgBZJPR58tVD9ttfcc7DBWl6vVM4qWCg4LGGIPG2lv0ICqEdU1r5BLP55YVnYpVByHLzvqLQJqp2D4vnp3nHXcONC2CIRqxiG+yg5xNWcQsfVsjFtMLVTw/5PC+7Jaf41YmBbIQQgixB7l+QNmN/pkf7E3ieCHZjIVh6GSSJmYszVJuaVeykMfGp4mne+ntSqw73wvQlY1mgUtVvy3rph03AHU9k3hhWQYyAGrtLXp1lqnTlY5h6NrK+DQNvGVz00opKhXvpgvk51+fw/ND3nv36sN5jedGYRhNOsi6tio6TtM0urNxlopbL5AnZ6Mc65H+9Jaf41YmBbIQQgixB7leiKeSoEL6uhLYrk9vbaFFV0cCTTeYn8/tyrrpmcUymqbT2xlfNyECoK+nk8CrUqq4bVkWYrvBihGE+VxUNDZGLNbZoldnmUaj67xiAYfSVnSQPT8kCFl3EUgzr15cpL87wYGhzNoPUs1HQZp1kCGKsNtMB/mpr1zmN58+s+rjE3NlDF1jsDbPvNdIgSyEEELsQa4XgNWFSRXTiA6SZVLRMoferqjrN7ewRHBjBlibhaEiX44qtp6O+LpLOAB6e3twK4sUK170M7VYsexiLltUspC30TXoqr2YALVmDF1dfVtdf3eCuWXLQjSNFdv0XD+MdlDfhDBUXBjLc/Jg17qz2msV8oaho+k0Rmzqujs27iDbbsBXnp/ku2fmV937ybkKg73Jdddi38725k8lhBBCvMnNL+SJZwZJWT5hqDANvZYaAQO90dzoUq5I0MZs4WYc18NTtU52Nr7hiEVvby92eZF8ycX1w1WF3nYVKysziRfzNt0dcQxdi76Xtv4MMlzfVtfXlWR+yW5co6FrUYe6xnUDUDfXPR6fLVN1Ao5vcBhOQ1uzkLcMfdUoTU9HnELJXTcL+cUz8zheSBgqrkwVV3xucq68Z8crQApkIYQQomVcL2B6vrLblwHA1fFJUp376ErrVB2f7o5YowM51N8FwFK+vOMjFmPjkySyQ5haQDJubjiP29PTg1tZIle00VAtvd4gVJTtlTPB87nrCRZ+oKLc6A3WP9e31fV3J7DdgGIlOhxpGBrOsmUhZdu/6QSLc9dyAJtIi1BrdnMtU+fG29bdEUcB+aK75jN+8+Vpumud9IvjhcbHq7bPYsFhnxTIQgghhNjI1HyFibnybl8GABcuTWFYcQZ64nh+SFf2emzZ/pF+AArF6o53kK9eGyPZOUw2BZq+dtezbnBwEKeyRLHsAdq2t78tFx36Wxkzt5C3G4kUvh+SjK+92a6uvq2uvzuax52vHdQzDZ3qsqSQStXDvMkDeuev5envTjQOK65FqbVnpS1TX/XCorv2fItrjFnMLVU5P1bg/W8bZqg3yaVlBfJk7UXgSH9q0z/H7aatBfKhQ4e46667uOeee7jvvvsAWFxc5IEHHuD48eM88MADLC0tNR7/yU9+kmPHjnHy5Em+8IUvtPPShBBCiJYqlCr8hfu/jyd/5z+vmDvdDUEQcm0qB8C+wajzWM/5BTiwrw+IotN2uoN89co1kh3D9HUmAIWhr1+KHDt2DLeyhBdEi05auSwkGn+4/nyeH5IvuY0ECy8ISSc2LpDr6RH1fOH6HLJhaCuSN0pVf8ORkuXCUHF+rLDhprowjDYSrtXptkxt1YhFvTO8VGheIH/rlRk0Dd71lgGOjHZwaaJIWBsdmay9CJQO8jZ8+ctf5nvf+x7PP/88AI899hj3338/58+f5/777+exxx4D4PXXX+fJJ5/ktdde45lnnuETn/gEQZsCwYUQQohW+/V//585+8bLvPHay7teIPuBaqQpHD3Qj4IVc7ad2Thh4FNxArw2HHxbz8Ur10hkB9g31BlFqG0w33v06FHcag6ICsxWrpsu3XBAr55h3Ltsi158Ex1kQ9dQta/ToHHvdU0jVIogCPH8kDAMbyrBYmK2TNX2NxyvCEK17qiKaRo3VSCHSvGtV2Y5daib7o44R0c7qNg+MwtR53hyrkw8ZtDduX5X+3a24yMWTz/9NA8//DAADz/8ME899VTj4x/96EeJx+McPnyYY8eO8dxzz+305QkhhBA3rVCq8Gu/+q+j/7+w1Ja0hZsRhIp8KcB3K+wbGcQy9RVZvqahE3plXI8dL+avTS6i6wb7h7rRtI1HLDKZDKlaHVYst3bddL7sEl/WWX/+9Xk0WHEgbjMd36jIj4rU7o74iixkDQ0vCHG9gJs9X3juWh5uuJ5mglCteAF0o1iTEYtEzCCZMJsWyOeu5lgsOLznrVHu8tF9HcD1OeSJuQojfSn0DWazb2cbvyzaBk3T+OAHP4imafydv/N3eOSRR5iZmWF4eBiA4eFhZmdnAZiYmODd735342tHR0eZmJhY9ZyPP/44jz/+OADT09NMTk6280e4bc3Nze32JewJch9bQ+5ja8h9bI123Md//x9/k+nJcdLpDEuL81wbm6DSldj4C9ukXPUo2uCUZ8jnl4iZOpOT3orHqKCK48PU9BSmKq7xTGvbyn1USjE5m0cfgYRhk1ucY3bG27Cr2tcVzbrOzi0wMaHhlLefvRsqxfT0EpmkhUY0pvD1701ydF8KzcuzOJ+nWPFYyHgUNshqdtyA/GKe0LboSutMzRVYnJ8BoFj1mBi38QJFPlckdKwVX5vPLa75vK9dmKGnw0K5ORbn1/7+thuQTVlMWs1XRxdKLrnFMoG9suzrSOnMzF+/1rqvfGeKRExnf4/P4vwMplKkEwavX5jl1D6N8Zkipw9nV33deopVj6kpf8MDj1vV6r/XbS2Qv/71rzMyMsLs7CwPPPAAd9xxx5qPbRbb0uwmPvLIIzzyyCMA3HfffYyMjLTugvcYuTetIfexNeQ+tobcx9Zo5X3MFyv85mce5+577mVoeB/nz58lle1lZGSj1IH2WSw4BHoG5c6Q7eijvyfJyODKJRMGPp4Wo6O7n5GR7i19n5u9j64XUHFNMsDhA8OYps7oaP+GX3f00D5mAKWn6OweYGR4++uNK7ZP55JFVzbKhn790hL5ss9PPnCMnr7omvSSw/79AxsW8K4XMFeO05WJMTJY4HvnFujpG2w8R09fFxXbo8dPkq1lUS9Xf+xyoVJcnbnEPSd7m35+uWLFZag3xchA80Ui6ZJDwcvTlVn5vfu758iV3BXPX3V8Xr9ygffcNcjg0HDj48cOLDI+V8ZM9lB1znN4dOPrWk4vOQwPb3wvt6OVf6/bOmJRv9CBgQF+4id+gueee47BwUGmpqYAmJqaYmBgAIg6xmNjY42vHR8fl38IhBBC3PL+0+O/ydTkGH/vZ/8RnV3dFPI5qo6/8Re2Ubnioswslirjh4pUk4NmlhGAHsdrw3a6tXh+iBPEQHmkEsamEiIATh47QBgGLOXLLVs3bTv+ig3MX39pmnTS5K3He4HooGPcMjZV0Bm61ljG19eVoFTxGr8DGhquF1CqeBsuRVlucrZMxfY5sX/jF1phyLojFoau0+yn6O6IrxqxuDpVxPND7j7Ru+LjR0c7mFuyOXMlB8C+gb17QA/aWCCXy2WKxWLj//+f//N/8pa3vIUHH3yQJ554AoAnnniCD3/4wwA8+OCDPPnkkziOw+XLlzl//jzvfOc723V5QgghxLa5rsun/t0v85a3vp33f+CH6ezsIp9fomL7LV9ocTPGZ8pomkYq5oNqPkebsEA3Uzs6g2w7HlgdxDQHP1Ckk5srkE8cP4ZXzTEzt4TTovnuYsVrZBKXKh4vnVvgnacHGofdvEBtuoDXa4f0VC0LGZZHvUXLQsq2v2Hm83KbnT8GUChMY+3iu36I8EbdHXHKVX/FzPzEbHQQb3RwZQFcn0P+2otRk3MvR7xBG0csZmZm+Imf+AkAfN/nr/7Vv8qHPvQh3vGOd/DQQw/xmc98hgMHDvC5z30OgNOnT/PQQw9x5513Ypomn/70pxuxKUIIIcSt6A//8A+ZGL/G//FLv4ymaXR2deO5Lk61guuFKw6A7aSx2SiGqzujA4qYtfo6MkmTopbBrtqEoWrrW9914+NTJLJDZJMKP1CNzX4bOXHiOM7vf4WFXAa3RR3vQtlt3JdvvzpLECred/dQ4/O+H5LMrh6HaEbTNExDI1TXs5DnclX2D2UwDJ1SxcMPwg0TO5Y7dy1PX1eCns6NZ9nX26IHUdxcsxOCPdnrSRaDvVHBOzFbpiNt0ZFe+bPvH8pgGhoXxwt0pK2moyJ7SdsK5CNHjvDSSy+t+nhvby/PPvts06959NFHefTRR9t1SUIIIURLvfzyK+i6zvt/4IcAKOv7yfQeJp/P4fmju1cgT0Xdx/6uqABq1rnsyMSZcQ3mFxcJwn07UiBfunqVZMcQfZ0KBZu+PydPnsCt/CHFyjBBGG67oA+CkKod0JWNoZTiGy9Pc2g4u2JswA9DkpvIQK6zzGidc3/tcObcDR1k7SZWTIdKceFaftWYw5o2iMszdI1mMxaNqLfi9QJ5fLbUdHzCMnUODme5OF7Y0yum62STnhBCCLFFV65eoX9gGNM0uTpV5OxCP/vf+mEK+dyuRr1dm8rhlBfo6+slETebFpPdtc7k7FxuVUZuu5y5MIFuWOwbiMYGNjuTm8mk0ZWD42m0Ypue7QaNevHqVInJuQrvvfuGA2eKpp33tcRqBXIibpJOmCzWZnsNXSMIFErb/D1eyNmUbZ/D+zZ5GFFjzTXTQO3Pv8nvQCMLOVo3HYSKqfnKmvPFR0ejMYu9Pl4BUiALIYQQW3b1yjWGRkYB+OOvXQMg1bmPSrlA2d6dg3pKKWYWK1Tyk3R19zU9oAfQ3x0lHiwsFVq6vnk9VycWADh0YACN9Zdb3Cid0An1BGGotr0e2/XCRsH63GuzWKbOfXeuTtO4meuzLL3xQqOrI06utsJZ0zT8QN1UZvBUfZVz32Y7tWrdEYv6CMiNWchd2ZXLQmYWKviBYnSNNIx6gbyXN+jVSYEshBBCbNG1a1cZHh7l8kSBVy8uYpmQ6tpHsZCnUvU2foI2CEJFqRrglObp7O4lnbSaPm6wP+riLuaLO1Igh6FidiHK6T20vx9d026qAO3uTKJpOpWqv/0OsuM3CtYLY3mO7MuuPpCn3WSBbBqNArQ7G2Op6DY+FwRh0270t1+Z4c++tzoHeXIuKpCHN9GpVUqBpm0431wfAbnxY9mUxVKtmJ+oza6v1UE+dbibv/R9B7jnZN+G13W7kwJZCCGE2ALf95mcnGBk337++GvXyCRN3veWLqx4hly+QNXZnRELzw9wXHCqS3R195FYY85331APAIWijb0D1+oHIflKSBh4ZFMWiU0mRNSNDHQBMDO3sO1temXbxzJ0qo7P+GyZo6MrkyLCUGHo+rpjCzdKxK5vq+vKxskti0/r706s+nMIQsUffuUKX35xYVVnd2q+THdHfFMpGn4tbWOjBRyxJgUyRGMWi/lagTxXxtA1hnqbL2KxTJ0f/f6Da74rsZdIgSyEEEJsweTkJEEQkOk/zuuXl/jge/Zz9EBUdM7lHFwvJNih0YXlCmWPEB23kqO3p3/NfNyDo9EegnLFoWy3v9vt1jOQvQJhCMnEzR1gPHwgmhG+fHUSP9heQV+xfUxT5/JEEaXg2P6OFZ/3g3DTEW91MctoRKl1Z+MUK14jQq9Z8Xrm8hL5kovnq0bntm6ytsp5Mzw/JLWJe2muUyDXO8jjM2WG+lI39cJgr5I7IIQQ4pY1u1jllQsLvHZxkdcvLTE2U9rtS2q4di2aOZ5z99GRtviBtw9zcCQqkHOlEFAtiyS7GQu5KD2BoEIilVrzoNnIYA8qDKjYPuVq++elfT9EGRksrYofhKQTzUc/1nL6xCEApqZnsd2t39cwVNiuj2lonB/Lo2tweN/KAtnzQ1KbjKCrW37gsKsjikDLl9y1Hs43X5lpvHi5NFFofDwIFdMLlU2NVwCbvpcxU1/VqQboWbYsZGKu/KaYL94MKZCFEELcspYKNn6tCxeGIbMLlV1dwLHclStX6Bw6xUxB54Pv3k/MMujtTBAGHkVHB03D3cElHHUL+ahATsaiBIW15mgt08B3y9huSNXx255kUa44WKk+sglFGG4+4q3urrccA2B2Ib+tbXqeH4KKuroXx/LsH8ysGn/wA3VTEW8QxbnVW8jd2evxac1UbJ+Xzi3wnrsGyaYMLi8rkOeWqviB2vQBvc3eS9M0CJv83enuiGO7AXNLVXJFd9WCkDcrKZCFEELcsqpOQCJmYJk6McvAD9WObn5bz+XLV+gevguA990TLZjQdQ2/uoAdxNEAx935JIv5Wgc5kzRJrtNZ1HUN5VdxfC1ah+y3Zg656virRgYA3jg/jmEl6OmMoXFzB+AA+no6CLwquUJ1W6u8o/g9Dc8PuTJV4liTVc5K3XwBb5k6mh4dmqunQ+QKzQvk774xhx8o3vPWQQ4MJrk4UWx8rpFgsckOssbm4uhilt68QK5d66sXo8OC0kGOSIEshBDilhSECscLMJbNQ+patHThVnD5ylU6+w/SmYmt7EC6SwR6FtPQqOzA6MKN5nNRUdaVTWy4yllTDn4YXXurxkFcL2h0sZf73c89BcDJI6Mobr5ANg0NgiplO8B2gk3Nd08vVFaNFbh+CBpcmy7h+eGq+WNgSwW8pmkkYgZ+oOiubeBbnmSx3LdemWW4L8WBoQwHBhIs5OzGOMbkXBkNGN7kDDLa5uLyDF2DJstK6lnIr15YAtZOsHizkQJZCCHELcn1ghWHm8IwKmx2oyvbzLWrV8n0jNLXtXIVsEUFzepE19iVLOTFfJUw8BkeGd7w8Jap+YTEUKhtjS0s57gB5Yq3YlHKhQsX+ML//BIA9739LjR9KwWyTswIcAMDFBu+UCpXPa5OFVfF7VVsH1PXuDgebRs8Mrq6QN5KAQ+QjJn4QUgibpKMG43Z3uVmF6tcmijw7rsG0DSN/YNRYkR9zGJqvkJfV2JTXeFQqU3H5a0VA1cvkM9dy5FNWXRm9vYK6c2SAlkIIcQtyfNDxq5e4onf/I98/Kc/wt13jPBffuNTFCu7ky98o2vXrhFL99PfvbJATpoumm6QL3vYjr/jM9NTs3nc6hKjoweIWet3kOOmAjOBZehUWlTMV50A1w8bBaxSik984u+R7IzGUOod941iyW5k6BrppIFuZcnllzYcs5hbqmI7PsXyyi5upephmjoXxgoM9iTpSK8sCJVSWyrgIUrmqGc0d2WvLwtZ7luvzKBp8M7TUYrISG8c09C4VBuzmJy7iQN6frjuGM1yhqE32zZNZyaGpkVz19I9vk4KZCGEELekP/zD/8FH/tJ7+Bf/9BeZnBgjkUhw5vWXKFV2v4OslGJ8YgrNzKzoIHt+SMKKCsO5xSpByI7PTM8vFnErS4yMHloz4q0uldAxrDSmobUsyaLiRAkR1VrB/bnPfY4vfvF/cs87f5hsykLXtJuOUINohKGnM0081c30xBVK5bVfKPlByNySTU9HgoUburhl28cwNC6OF5rOH/uB2lIBD5CMm9QnP7qz8VWH9EKl+Pars5w61N2YU7ZMnf2DGS5NRBsNZxarjGxyDvhm0jYMXWu2bRpD1+iqdY2lQL5OCmQhhBC3pG9+41tYVow//dr3+Pyz3+atd9/LzPQktus3javaSfPz82ix6K35/q7rSxVKVY/OdPRP6+R8GbSdPVQYhopC2cWpLDG6/xCxDbqgHWkL3bAolitUba8l3e6q7ZNKmORLLoVCgZ/7uZ/j7rvvoXvgEL2dCbwgXHO730ZGBrsx42nGrl0lv06BnCs6KBTxmEHVDhrjHkEQ4vkhs4tVKrbfWJ283FYykOtM83qXtqsjRu6GGeTJ2TKLBYd3nF651vrIaAdXp4pMzlUIQ7Xp+WM/UKRTm7vWaBV18z/f+pjFqBTIDVIgCyGEuCWdPXuGg4ePsn//QQAGh0eYnppEKXB3+aDe1atXSXZEIwP1DrLrRYkb/b0duNUC49N5QNv21reb4QchtgeenWff6OiKA47N7BvIAHDm/DiB2n63OwgVvh9tditWPT71qU8xPT3Nv/mVXyNXdOntihOGas3tfhs5vD9aFnJtbBLHa75yWinF5FyF1LIit94dd70QjWi9NKxeEALRIb70FjfFWaa+YllIoeSuOExYT/c4OJxZ8XVH9mXxA8Vzr84CbLqDrNhcggVEB1zXev1TL5Clg3ydFMhCCCFuSRcvnuPI0eON/z00NML83AyB7+16ksWly5evF8i1GeRy1Wf/YIb+vl4q+QmmFyqg2NFut+uFBMoiZgRkUokNH3/H4WgO9uLVWVqx2MTzAzQtipALAsVzz32HO+64gzvf8raoQO5MgAbWBqMfaxnszwIwuxgdaGv2e1Cu+lQdv1E4WqbWmAV2/QA0jYtjBTozsVUHLJVSqBC6O+Nbur6oY3993bRi5bKQibkKpqEx0L1ylfOR2qKSb706g67BYE/zVc+rKEXM3GSBrGsYRvNtev3dSSxTZ6h3k8kZbwJSIAshhLjlVKo284tlMod+hN995gK/98WLlOJ3keo+wOL8DJUdWI28niuXow5yzNTJpqyoexw36crGGejvpZKbYLHgomngeTtXzC8VbNCia4pvorN4152HCHyXybkiKG1F8sRWeF54vUupFK+9/hqnT59mZqlKECp6OuOAtuHox1oGai9GcoUoRq7a5GDh7GJ1xfMn4iaLRQeloqQODbgwXuDY/o5Vc8blqk9fV4JEbGsdZMPQMfSoCG0W9TYxV2aoN7Wqs9+VjdPTEadc9RnoSW7+gKDGhnPmy1lrbNP74LtG+UcP37Olg4l7ldwJIYQQt5w3zpyl/8j7yIUjvHBmjm+9Ost4oYOD93yEhfkZSrucZHH56lUy3fvo706gaRpl22f/YBpd1xgc7KeSG6fiRMXxTm7Tq2cgd3ekNlU4HTywn2p+koViEB3U22aSxfIRDde1uXL5MnfeeSeTtdGC3o7rB9O2orc2712s+sRMg2Jl5Yyv6wXM56uklo1IGLpG4IdUnYBK1adqeywVHA6PrByvUErhBeHm84fXkIxHUW9dtZ91eZLF5Fx5zfGJw/ui7vhmv38QKkxD33CMZjnL0pvOmScTpoxX3EAKZCGEELec118/Q7JzhGRM45d/7j3823/wHg4Pxcj0HGR+dpJSdefj05a7evUq6a5R+rqTOG5AKmE2UgkG+nup5CcBmM87eC3aULcZ41PRNrSBvi5im5jzTSRiBPY8FS+GaeqrMoNvVtXx+eK3xxibKTE5dpkwDDl9+nQ0bgJ0ZuNbTogA6OmIgwqxPZOYpVMorbzehZwNaKueX9M0ShWXsu0zn48K1n0DKwvRiu3T2xm/6RXTN0rE9dqykJXrpstVj1zRXfV96+pjFpudP44i3m7uWi2jeQdZrCYFshBCiFvO62+8TqpjmIFlM5GH9nWT6hplenqaINjdldNjV8ewUr30dyWoOD6jAxn02iKGgb5oxAKigs1r0Ya6zTh3Ofq+I8MDmxpjMHQdiwqhnkEpte0O8sxilS99Z5KvvTjFtcvnATh5xynmlqKRiI60teLw3M2KWQYWZczUIBoKzw8avweeHzI+WyabihIyxmZKvHE52g4XjxksFhwqjs/MYhWA4b6Vhajrhas+thXJuFVLwjCIWzq5Qm1DXmOFdPPvceJgFwAHhzJNP38jzw9J3+S9jJnNZ5DFalIgCyGEuOWceeMMmZ79DPVeLyYOjXajGybjM9EBrVZtftuKmYUCmm7S1xWNWCSWZdEO9PdSLUwBirlcdUdHLK5NzANw8MDIpt56N3SNbEKhaRoLeQc/CJsmQ2xWPaXh2lSJixfOYBgG+/YfZqngRBnIukZyg+1+6zENjY6ET7b/GAvzc4QK7NrCkPmlauNnUkrx2//3WT7z9BmUUsQtnULZRYUwPV8hnTDpSF+PmqvYPt3Z+Jbj55ZLxAxCFd3T7o7rWcj1MZO1CuTRgTT/30fu5S3Hejb1ffzw5jvI8doqbLGxDf/2/Pqv/zpLS0s7cS1CCCEEAOcvXsZKdq847T9aiySbz/ugqV1LsiiVSrgqOizW350ExYpurWVZpFNJDFVhbsne0QJ5dqGI71Y4fPgwprHxGIOua/R3R6MAk7MlNKVt+YWHUqoxSjE+W+bcuXPsP3AE19dYKjr0diYIAracMQzRIbiBLhMr0cHFq9PoukbVieLeJuYqZGrd4wvjBSbnKpSrPrOL1WjkQmmgKabmK4z0p1aMYThesOntdRtZPl+9fJvexFyZZNxoHN5rZrA3tenxEw2N+E3G5cVjxppRb2KlDQvk6elp3vGOd/DQQw/xzDPP7OrMlxBCiL1PKcXUXJRT299zPYZroCeJCn1KbhzL0Cnv0kG9y5evNCLeejrimKa2OpWguxvl5phdrBL44Y7925krOvh2gY6OLsxNHt46uK8XpUIuXptFaVuPevMDxULtkGAQKsZnSxw5dpJi2WWpEGUga1q0TGOrDF3j0L5o+92FawvEDJ1C2WNuyUYpFW2LA776wlTj/6+vcLZMDQ2NyfnKilGKIFSYpt4orrfLMvXGPo7ubJyl2ia/ybkKI/3pLc9f30hx84cdTVMHTeq4zdjwzv6zf/bPOH/+PB//+Mf57d/+bY4fP84//sf/mIsXL+7E9QkhhHiTuXptDD0Wvc28vINs6BpmWCA0u4hZBsVtHijbqnoGsgZ0ZKymb3N3d3XjlWeZWayiUDv2tnbVVejYKNSmOsgQJVnYhRnGpvPomtYYWbhZnh+yWHAa37fipzh+4iSlqkeu1kFWSm07SuzU0WHCwGN8tkosZpAvuUzMlskkoz+HQtnlxTPzfN89QyTjBpcno5GcdNJCKUXV9ld0i23Hpzcbb1nhapl6Y6VzVzZGvuQShIrJuTL7NnkAb3PUppeE1EXvdLTm59zrNvVbqmkaQ0NDDA0NYZomS0tLfOQjH+Hnf/7n2319Qggh3mReffV1Up3DAKsWKmRiHlZmGBVGyyB240T+lStRBnJHxkQpmh466+ntoVqYwfNDKtWAIGz/mEUQhAQqRsKM5l/rhwY3cvDAQcq5ceZzbtSZ3+RBPeeGzGTPD1gs2BwYypKIaWT6jnLijlPM5ezrGcja1iPe6vaPDlNauMxCScPQNTw/JFRho4v/zZdnCELFD9w7wuGRjkYHGaIuLsDIsig1178eydYKuq4RMw2CIKS7I06o4OpkkaoTMLJGgsXNCoKQmGk0uuSbZRo6KLVL0wAaLXoNsiM2/C391Kc+xb333svP//zP8773vY9XXnmF//Af/gPf/e53+YM/+IOduEYhhBBvIm+88QbJzhHSCWNVd7a/0yCe6ubKtUnYpZXTV65eJdU5zGBvGj9ovja5t6eXcmEOgHLFI9iBDrLj+uhWhkzKJGbqm+6IHj58kHJujJJjoGmbO/zo+SHXpopUl3WbXS9gMe/Q350ga9lk+49x4sQpFmtjFz0dcQxN2/Tox1o6Mmns/DUqfpJQKZJxg2wqmusNQ8VXX5zixIFOhvtSHN6XZXK23LjOqVqSxPIOsgYtOZy3XDJu4AWqEf332qUofq9VHWTPD1dkPW+Wrkdzyzv9wtIPwm3F++2GDX9L5+fn+R//43/whS98gZ/8yZ/EsqJfIl3X+eM//uO2X6AQQoj2mF2sUCy7Gz9wh505e5Zsz/4VEW91+4ejrNgzF6Oc4Z08AFc3du0aqc4R+ruSKEXTg1I9vd0UczMAlOyd6XSfv3QFM56mpzO1qQzkuv7eTnBzKHTyJXdThx8rtk+x7DFfi28DyJc8CiWXvq4EQXWaTPcBRvYdIlTXVy8ntnFAry4eM9C9BZRmMbtYJRk3G53U1y4tsZh3eP/bo3cgjuzrQAFXJqMu8uRcFANXL6gdNyCTslq+QS4ZN6MOcu1A3msXo7CDzWYcb8QLbj7BYvm1+Tv892arBf1u2vA34p/+03/KwYMHm37u1KlTLb8gIYQQOyNXdBvZrLeSM2+8Qbpr36rxCoAThwcBuDqZB41tRZJt1dWxacx4NtqiR/ORgb7eXvILURFfru5MB/mV1y8BtSUhN1HwxSyDlBXNc88uVgkCRbDBfS1WXBJxk+mFSuPPYHKujAL6uhIsTb2BphvM5HwW8rUM5JR106kLTa83ZpAyoki3q5PFFZ/76gtTdKQt7j7RC8DhkSwacLk2ZjE5X1k5f+wF9HQmaLVkIopTq3eQr06X6O6It6RIVCqaae/Z4lhIYhei3jw/bHmXvt0kB1kIId6kbDdgMW+veJv8VnDh0hWMeCcD3UmKZZdc0SFfcsmVXPr6hnDKC8wsuZi6TmWbiy22YqkUfc++rsSaSQI9PT1USwtA1G3diUL+/KXakpChgZs6vBWzdHo7o07n1EIVTYs6lOtZKjgkYgYKxWK+ntIQ5fz2dSW4cuabAFydKrKYr2UgG1pLCkTT0OjKmoS+w9XpUuPjV8bnefXCAof7/cYYRzJhMtyf4uJEIUpHma8wsizBIgxVY7FIK8UsAwWkk2bj92Nkmyus60pVj/6u5JYLzmTCxN+Bmfjl6qMwtxMpkIUQ4k1IKYXjBZim3ujw3Qry+Tzl2uX09yQIQsUdh7u563gPdx3tIZ3NUM2PU6gaGIaG4+zsDLJSioobFXl9XQk0vXmB3N3djWdH6Qll28P12n+dV8ZmARgZGSAR2/w/75apMzI0gFvNMT1fjlI3/LU7jJ4fUrV9TEMjnbCYnCvjB2FjQ11HUuPyuZcwcbg6VWIhbzcykJvNa98sw9Dp7++nOH+JK1PXO8hPf/kcQeAxksmvePyRfR1cnowKdccNGKl1kOvxbu14698yDTQVhRzUV07vG9j+eEUYKoJAbeuwX8za+SQLTWk3nbix26RAFkKINyE/UKAUmaTFzEJ1w7fUd8rrb5wh2TkC1BIsNEglTBIxk2TCJJWwwF3E0zJomkbV3dkOcj6fx0xGEXRd2fiaB496enpQYUDMhErV35F105OzUWHYlYljGpsvRjRNY/+BA5QXrzE+ExWc63W8l3ftLVPHqR3OWyo4WKbO9MQlwjCkNwvXposs5J2WZCDXxUyd3v5B8rNnGZsuEQQh8zmbs+M+k298gdOnjq94/OF9Waq2z4vnoi2Dw7VOru349LQw3m0509BQ9ai3jqg734r542LFY6Q/TSK29aLeMnehUNVUrTC/fdxeVyuEEKIlokM6UUyWH4TkS7fGYb3XX3+jEfHW25nA0PUVqQfZpEXSqIJmsJC3d3zd9NTUFMmOYSw9JGbpa26F6+mJimjLUFRsv+2HCV0vIF9yUEqRTsU2nYFcd/jwIcq58agLrFi3412suBjLnj8RM5ieL7OYd+jtjHPu3FkAjox2MbNQZSFntywDGaKifHBgmOLcBfwgGpv4wjfHUCgmXn2aAwcPNx67WHQ4NJIF4OvfmwauF8heoOhuYbzbctHvbNSFb3SQt7mpLwhCNC3atrcdlqmjsXMzyGGo0G/4e3w7uL2uVgghREt4wfXtbqm42Yi/2m2vv/466a7RxuxmKrmyAM2kLTpT0XVPzpVrB5Z2rvs9Pj5BsmOQjrSOH4Sk13h7vl4gm7pPuerjtblArtg+VRcMHHT95qPUjh05RCU3jutD1fGx1xldieaPr//cybhJ1Q1YLDj0dSW5cP4MhmFw+vgoimiUoaejNRnIEHW8D+wfoTB7HoAXz87zzZdnIP86I4M9jbQt2/HRgK5MjHTCZHqhSmcmdn12V6m2JSvU/wzCUDHQnSRu6dsubItVj9HBzLbvoWlooGk7loXs+eGqv8e3AymQhRDiTcjzw8YYYjxmUK56lHdpM91yZ8+epWvgMIM9SfwgXLWEIxEzGerNEAYeY9NFlKLtxedyE5NTJDL99HTECQKIr9FB7u7uBkAPHUpVr+3XeG18Bs1MEzejose4yQ7y0SOHKS+NAzCfc9YcXanPH99YpCUsnaWCQ19XgssXz3Hg4GFGhzoan+/ubE0Gct2RQ/upFqYx9ZBnvhld99Xv/QFHj51oPMZ2A7qzcfxAcXhf1EWuH5RzvSjerZ1zsXHLwA9C7n/nPv7x33r7tgrbUCk0NPq6tp+4oWnajiZZeH5IugXxfjtNCmQhhHgTsh1/xRYu09CZW6ru4hVFLl++RCI7SH93Ej9QpBIrC5iYpTM4NEw5N86V8SU0TdvRAnlyaop4upeBngwA1hqFaL2DTFilVPFw/bBtHTulFK+8fp5YsotsygRUY6vcZg0O9hHa0YzufK6K4za/p/X5Yz8IV3TugzAqSPu6Ely6eJZTp+4kHjOj7XlEc9FrvZjYioMHRwFFQisRhop3vaWPy+de5EitQA6CaLNeX3eSUMHhfVGxXo94c7yAzkysZdfTTH0hRzxmMNCzOrLwZthOQHdHvGUvMJIxc8feefFDRboNSSHtJgWyEEK8CVWdAFO//k9AKmGykLN3aQXtdTOzC2hWloHuJAqIWSuLqphlMDS8j/LCFSYXqijFji49GJ+YxYyl6O/NomlgrXHwKJVKEYvFUF6ZUtVHqZCwTctCbDfg5e99l3iqm/7eDgxdv+kVxHHLpKcrDSogV3RxvKDp70J9/vg/fO5Vfvvz442Pz+fqWcca49cuc/r0aQAODUed24601ZIEi7re7g5S6QyaM41paNwx7BKGYaODXLJ9RvpSUbSYgiO1DvJwLeItCFq/Pe9G8ZjRsvxrxwta0j2ui3Kad+jvjeKmcrlvFbffFQshhNi2ybkyf/y1q41/JHVdI1BsaotauziOg+1HRUt/TwKUavoP6+FD+yktXqVsg+P5O3pQb2qulhSRjaNQayYCaJpGd3c3gVMkDBW2E7TtLe1K1eObX/8SsVQ3Q/3dW3orX9c19o3ux7fzLBUcqC2juNFSwUGFitcuLnB5yuZqLWatXiDPT10kDEO+733vQdPgPW8d5PvfNoRhaC3NwY1ZBgMDQ1Snv8H/+TP3Mjd5EYCjR0+ilEKF0NOZIG5F67OP7+/kJ3/4CPed6oueQGu+AbGVEjG9JRsUVW28ItPCLmwybrJzo/vqtot4AymQhRDiTen51+f40vOTvHhmftlHFdVdWLxRNzk5uSrirVmH9uiRg1QLUSJBseztaNTbfG0MJZsyiZnGup3anp4enGq0YrhsB21bNz2zUOLFF19ANywy6RjxLcZpHThwgGpxhsWC07QzX58//t3fewpNjzr7f/rta8D1Avn8a88B8H3f9z4ScYOTB7v4qx86ThCyZuLHVg0ODTE7Nc5AT5JLF86haRqHjx6j6gR0ZWPRSmpdI520CELFD71jH4m4WSs4oxnhdrJMoyVZEbYT0J2NtTQFwjT1HUlCVkqBprV8lfdOuP2uWAghxLYEQchLr7wBwB99+fXGxy1DJ1dyduuyuDY2vm7EW93wYB/4UecyX3Kp2jvXQS5Uou+VScU27Ij29PRQKUQvQCpVry1Z02Go+OpXv0ZINOubSZhbLvwOHTxAOTfNQr4azXbfcL0V26dYyPP5Lz2HUiFT577EC2cWyJdc5nM2HWmLF7/7DU6cPEVPTw8d6Viju6/Rmgzk5faNDDM3OwPAxQtn2Td6gGQyheMGDC3bWpdJmrjLcqg9PySVMNFvcgzlZi2PetsOxwvpbbJ2fTssU9+RoDc/iDbotftet4MUyEII8SbjBSGzC7W3xosGf/aNFwBIxE1yRXfX5pDHxydIdo6QjGnErNURb3WJmFk7jBYVyDs5FmJ70T+b6aS5YUe0u7ubYi4q4EpVry0d5Krj842vfZl052B0XSlzy6MDhw8fwi7NkS95BIFa1UEuVVx+4z/8axLdR+nvNBh/+X8QhvDVF6aYz1Xp7Uzw0ovf4d3vfi8A2XSssdK4VRnIy42M7GN+fhalFBcvnOPosRN4fkg8ZpBZNl+cWXYdAK4XtmW99I1MU2MzG+vWO2QadWBbvw47+rNo/99zzw9J34YRbyAFshBCvOl4XkjV1bBzVwgDl0//1p8wMX4tWhrihzg7sBa5mbGxcVIdw/R1J6Iu3xoFaCxm0NedRQUeSwWHIFA7sgmwWq2ijDQ60Yru5AYZuj09PeQXpgAot6hALlU9zl3JsZi38YOQUiWaP77jbQ+gAUO9KWJbLJCPHIoKZKWgVHVXzXZ/98VX+P3f+x26h+/knjtGOHFkhOriGb764hTTC1ViukO5VOS973sfEC0QabzWalEG8nKjoyM4dpV8PsflSxc4euwkZdtjpD+1omMZHQ68/r/9MCSTbm+CBWyug1yx/XVjAB03oCMda/m9Mw0dQ9fbdnC0zvND0onbL8ECpEAWQog3HS9QKDNDR8LjriNZuva/m7/zMz9NIR8dQNvJkYXloiUcQwz1ZZpGvNUZusbwvlHcygKLBQdNY9U4QDtMTU0RT/eQsAKUYsODRz09PSzMjgHRuun1ttNtRhAE/OIv/CNeePk1zo8VePHMPC++epEL516na99bOTCcIRm3bnqLXt2xY0ewS3MAFCv+itluPwj557/0iwweuBs0gxMHOnnnu97LmW/+V0oVj3zJpZKfBOB93xcVyPFYdEAuDFVLM5DrRvdF8+rfff7buK7DoSPHMXSd3s6VaQ9xS7+hTtVamqixFkPX0NZZyOH5UVReTza+5u+G7QX0tzC9YrlkvP1JFgpItPBw5k5qe4EcBAFve9vb+NEf/VEAFhcXeeCBBzh+/DgPPPAAS0tLjcd+8pOf5NixY5w8eZIvfOEL7b40IYR4U7p0ZQIzlmagN8OPfuAUhpXAtvbz73/tl7FMnUJ5d9ZOT0xOEk/3RmuJWR3xttz+0X2Uc5PM56ooFL7f/reLx8ej68smo3/wN+rq9fT0kM8tYJl6tG7a214xcubMGX79U7/CP/lHf5d0HLJpi29/48sYVpJKkOHU4W7QFIa+tX/aR0f3obwSAMWyi+1cv95vfOPbPPfNP+OHfuxvo2lwdH8n73jne1iaeJlMPFowMzN2lv6BIY4fPQJEBWI6YVF1/C13tdczMhIVyF//2lei/73/KPsG0qsyoA1DJxE3lnVp1ZYPMt4MTdOIW0bTdw5CpShWPI7t7ySTia39Ak9FoyrtkIjvwLIQpYitkfRyq2v7b8iv/uqvcurUqcb/fuyxx7j//vs5f/48999/P4899hgQrRd98sknee2113jmmWf4xCc+QRDsXtyQEELsVd9+/jUADu7r59BIloNDGQ7f8+OcO/s68ZjBUnF3DupNzRbRdCPqAK4R8VZ3+NBBqsVZ5nNRqsROLAuZmJwknuqluyOBxsYztUNDQwAkYhoV28fbZoE8NRWNa5w78yqf+rf/Al3T+PbXv8KhO9+PUnDHoS5Au+ktenW6rjMy0AlAruRiL+sgf/eFFwEwMvvZP5ghlTA5cfJOurq6CeajGfZzr36Du9/2zhXRdx2ZGBXbb3mCBcDwcHSg87lv/TkAR4+dXDMrOJuycL0Azw9JxMybXqSyVXFLb1qE5oouBwbTdGXjJNZ4J8JxAzLpWNsi0pJxa0c6yLEdeDHSDm296vHxcf7kT/6En/mZn2l87Omnn+bhhx8G4OGHH+app55qfPyjH/0o8Xicw4cPc+zYMZ577rl2Xp4QQrwpvXYuiuY6deIQAO+/dxgzNcBsIUqNcN1w2+MAW7FUijqRvZ3xNSPe6o4cieZlK3aI74c7clBvfHySWKqbvp4M2iaiq06ciJZWGHiUqj7uNov4yclohOFd7/l+fuM/fYpvf/PP+caff5kT9zyAZeoc2dcRpUVso/g7fuwQgVchV3Dwg7DR/XzttTdIpLJMLricOBAV0YZh8O73/QDPf+m3+esfHOTSa1/j3ne8e8X8byZp4fphSzOQ6+oF8vmzr9HbN8DJoyNr/uyZlIUXRL/XHTu41S0eM1fNx5erHt3ZGEO1pSWmqYNa/aLG8aJV2e27NoOwjQdygzB6EblTL0Zara1HC3/u536Of/Wv/hXFYrHxsZmZmcYv9fDwMLOzswBMTEzw7ne/u/G40dFRJiYmVj3n448/zuOPPw7A9PR04z8YYqW5ubndvoQ9Qe5ja8h9bI1W3cdLV6eg8wA9WYvF+RmODCg05WF2n2Z2epyKC1euVVckAbSbUoqKGxVRelCimKswO7N20ZvNpLGLtX8/JqeJU0K56U19r63ex3MXx9CNo2STBuXiApOT6+cvd3ZGhaTv5MkXk8zNTjGZ2Po677NnzwLwi//nP+PvPfLX+V9/5mOUyyXM7CFGBhMUc3MUKx6zMx6atrUu8v7RUSYnZ5mc7SG/mGB8zMM0NV559SWOnv5+/EAx3KVYnJ8hn1vk7rvfxjN/8hRf/fwTAJy64+SKf5cdL8AuLVHMeUz6hS3/7M0opUgkEti2zf4Dh/DtJSYnc00fW7V98ksFQCOupZicLLX0WtZSyNksLlVxlh3oLFY99g9mmZ6OfhdySwsUyyaebbK8+V+seHTEqyi3PX8P6/cktNvz/I4fEjN1Jie9tjz/jVr970zbCuQ//uM/ZmBggHvvvZevfOUrGz6+2RB7s7/gjzzyCI888ggA9913X2MGSawm96Y15D62htzH1tjufQxDRb7kk8wGHDy4D73239n+zCuUh05TtV36BvaTTCcZGcq04pI3ZX5hETPZDcD+fUPEEyYjI91rPr6jowO7FBXIysyS6uxd9/E32sp9zJV9SMHQYC/DQwOMjHSt+/jh4WGy2Sy+U8J2FemOPkZGBm76+9aVSiVSqTSn7nwr/+ZX/zN/9Sf/IolML2Uvxl0nBunsGSCW9tm3r3/L3+Pe++7lz/7bWXLFo3T29NM70INpaEyMXeP09/8tAg3uOX2QVMLE80Me+Isf5l/+i3/C5/7775BKpXn/B35oxX0JQ0XOTjKyr4OONszSjoyMcOnSJe6++x72j+5b83GuF7BQSYCmOHCgZ8de/CXSNnZYoCt7/WfXSy4H9veQWlY0J7tS2I5PYtkoil5yOXSgt20jFrbrs1hN0Jlpz4xzseIy2JtiZGDn/jvSyn9n2tb3/vrXv84f/dEfcejQIT760Y/ypS99iZ/6qZ9icHCwMUc1NTXFwED0H4vR0VHGxsYaXz8+Pi7/oAohRIu5XkDF0zCxG8UxwKGRNKnOYd44d4l4zNjxhSHXro2RzA6QMAMUrBnxVpfJZIgbUQc3X/JwnO2PWHh+SGWdTYL1eedMcnNZw5qmcfLkScr5WUpVnzBkW1Fvk5NT9PZHecdvu/ed/OP/65P86P/yc0A0fxwE4ba3w9156hR2aY5cyQMVxf7l8mUmJ64R6zrSmD/2g5BCxWNgcJQDBw9TKhZ5y9330ZFZOQOs6xpd2Xjb5lDrdcK9b7tr3cfFLAPT1FCKHUmwqDOb5Q0rVh0SzKasFSM4Yagw9PZuoDMNHdWmLORQRQdnezrak8CxE9p25z/5yU8yPj7OlStXePLJJ/mhH/ohPvvZz/Lggw/yxBPRWzFPPPEEH/7whwF48MEHefLJJ3Ech8uXL3P+/Hne+c53tuvyhBDiTeny1atYiW4ySS2K5qoVhG87NQrAmUvzWKZO1fZ35OBb3djYBInMAB1pY92It+UGejIoFZArOrh+sO1M12LF4/JEYc1YrmK5vkXP2nRX78SJEyzOjeP5Ia4fbCuveWpqir5agQzw1//GIxy/5wEyKYt9A2mCUG27QL7jjpM4pXm8QG8canv5lTfQdBNbdTTmj20noCsdo+L4vOd9PwDA3W97R9OC7tBwhkSsPW9Y10c2T5++c8PHZpMW8ZjR8ri59ZiGDsteiHp+SCJurJrLTSZMlv9qOF5ANmVteVRms9ema1pb5pCLZY99A+kVXfLbzY5PTv/CL/wCX/ziFzl+/Dhf/OIX+YVf+AUATp8+zUMPPcSdd97Jhz70IT796U9jGLdnNIgQQtyqXn7pFRLZAQZ60ihoLIN4yx37CbwqE/P1DqqG7aw/Y9tKY+PjJLKD9HenNox4q9t/YBTfzrOYt0FtP8nCcXwW8w7lavOfu+oboBTphLXpbXUnT55kYSY6FFmuRBvqtmpyapLevusjGkopzlzJccfBrqjQCdW2O7XZTJqkFd3HYsXDdnxefvU1OgZOECqN47UC2QsUPV0JTEPn+3/ghwF4+33vxWpSfLazyKsXyMvTstaSScd2ZIPecjdmUq91SLCeGX39cSEdbRp9WC5mGdv6nWzG9QJMQ2d42brv29GOlPYf+MAH+MAHPgBAb28vzz77bNPHPfroozz66KM7cUlCCPGm9PKrrxJL3cXBff2goixU1wuIWQZecYxiujd6oMa2UxduxrWxCeKZt0UxYxtEvNUdPHiQ5yemWcgfgtqykDhbb6yUbR9dh9nFKpkbipggCFBaAkNzMU1908s4Tpw4gVv9k9rzb32bnlKKmZkZTn/gf+NrL05x76l+8iWHfMnljsNd0TWGqiV5w309UWFTLLuUqj7nzp2lczAqQI/s6wCipmgqbtKVSvGO9/4wn3v6WQ4cPb1u8kg7/PiP/zjFYrERqbeerkyMzA6vPb5xm54XhKSbFciWASiUUo0XFDvRfY1bOo4X0sqXDeWqxx2Hu2/b9Iq62/vqhRBC3JTX3riCpukMD3SCBiP9aSq1zXlJLY8W76Vc9TB1bd153FYbm1pE1w0GetMbRrzVHTxwgHJ+OpoNrs3LbkfV8enMxJjPV1fF3E1NzxBL9ZC0oqnNZp3SZk6cOIFrRxsKK9WAINzaNRaLRbRYLxXrKP/tmQv8o099i888HaVaRPnHEIZse8QC4NBoHwC5okPV8bl66QKDh97GUG+STCrKzo2ZOpal01vLHT5919swdH1HxxcAfvAHf5Df/M3f3FSXOpkw27Z0Yy26Hm0QXP7CqFkmtK5rJONmIzN5p2alE/HVMXTbUay49HYl6My0L55up0iBLIQQbyKXx6IopM5sjLil090Rb6wDHqqFQJy/lsM0NKo7WCDPLFQA6M7GN11oHTp4ELs0S6HkEYYhnr/1g3pKKWw3wDR1NDSWCisPKU5MTERb9FJR0bLZZRwnTpzAq0bxZqXq1kcspqamiGeiwvWjHzzK++4eYqngsH8wvWK1croFHdI7TxxChQETMwt4fsjVKxdI9x5rdI9tJ6C7IyqAYpZBf3eSfMltyzKQvSBhGdeLULX24oyOdAzXCwhChWlqbUuvWC62xqa/rVBKEQSK/YPZljzfbpMCWQgh3iR832chbwPRP8aJ2oGlod4UJdvj2P4ewsDjpTOTmKZOdQdnkPO1A3Cd2RjJTXbODh8+hF2cQxEVn/VO+FZ4fogKQdc0UgmTqfnKikN/0ZKQHro7oi1/m+2UZjIZejqTANE2vS12uScnJ0mkowL5rmM9fPQvHONf/v138b//9D2N64/HjJYUVafvPIVTWWRyeomq7TGzUEYzkxwZjQpkP1ArosEGepL4fkgiLiVFM7FYNOcbFb76mn9G6aSJF6janPLOdLpbuSzEdgM6s/FNz+ff6uS3WQgh3iTOnz+PleoBoCNlNTp+fV0JwkBx+PBhCrPnuDBWwDR0HG/7yRCbEYQK27dq1xUjsYkEC4BDhw5il2YAKJQ9Ktso6D0/pN4Ttkwdxw0oVq4vOBgbnyKW7KCvJ4Np6iu2xW3k+NEDqDCgUvUbhyJvVtRB7kWDRnFqGnojNcJ2fXo6W/O29h2nTmKX5lnIVbFL8yS6DgHX54/RVo4JpJMWPZ1xkvGdPQB3u4jHoi7tRoVvImaCUrh+SEdmZ+6laWhotOYQpe2GDHQnW/JctwIpkIUQ4k3ixe+9TCIzQDqugaaRqK3/rc9mDgztJzf1KgvFaNygFckQm2HbLspIY+JExdcmI8H6+/sJavO9hZJLZY30ic3w/HBFImw8ZjCzUKHq+ORLLheuRaMpg31dJG6yS3vixAk8p0DF8bfclZ+cnCSe7iObNpsefgpDWraIY3RkBN9eomTDxLWLdA2dImbCYG+yMX98Y5fw4HB2xTIMcV0iZuAHIZ7f/IBeXT3JQoXN55TbYbOz9BsJlULXIJveOy+SpEAWQogdsFa27k56+eVXSGYH6OtJoRQr3uod7kvR2TNEce4cCi3KA2ZnCuTxiUkSmX5SsRClIL7J4kDXdXq7oq7pUtGpzSFv7XodN1gRs5WMGyzkbV65sMjZqznGp6M54u6O1E0nRZw8eRKnkiNfqFDaYhE/MTlJMjvQdPGCUopQqZbMHwNYlkHSCvGJc/HCeToGT3FoOI2uaSvmj5dLJy2ZQV5D1OWPYvjWS6awTB3D0AmV2rExBcOIlqdsV9WO3sHY6UOa7bR3fhIhhLhFLeZtrkwWd/syeO21V0l3DdPXlQRN1bZ8RbLpGKZlkDEroELOX8ujoe1I1NvVsXES2QG6shZKgbXJA3AAo/tGCNwii3kHlLYqfWKzqrbPUsFuzGNqmkZvZ4KuTIyuTIxSxQWijWc3W7ycPHkSr5pnIV8mqM2Y3qyJiSlSHQNNi1PXC8mmrJYVJ6ah0ZmOoekm5y5Pkuk5wMnD0fzzjfPHYmOmqYMW/V7FY+v/GWWSFokWzZJvxo0xdM2EoWIhb687q+z5Kvrvyh4iBbIQQrSR7fpcmiiwVNzZ1c3NnD9/ASvZE6UeqJVvrxq6RiYVY3TfMG5pigvjBQwDqra3zjNuTxgqphcqvPDyBeLpPvq7U5uOeKvbf+AATmmWhYKD0hSut7WCfmqhyi//l5f48ncmm36+bEfPm05ZNx2/deLECTy7QKnswhavcXpqCivVQ1d2dYFse0F0eLBFNE2LYgCBsYXoZz062nz+WGzMrHVpdV3bMIYvm46tyuBuJ13XastC1v6dzJVcEjFjzd/bMFQYhraj170TpEAWQog2CUPF5fEChq4RBFt/+78VlFJMz+fRdIOejjhorOggQxSxNjJ6kIXxl7g8UQAF1W0kQ6ynYvu8cXmJq5NFFhaX0A2T0aFuNG5uLvLQwYMUlyZZyFVrIwBbG2G4Nl0kVPCV70427ZTZng7KJxEzmq5TXs/hw4fxnSL11xpbmUOenltCN+JNO8gqVC2f/Tx6KNpQp2WPgwo5OJxdc/5YrM+sjU2kN7E6ujMTY7BnZzux60W9Fcou/V0JBnqSa8YoVmyfvq4Exk0cXL0dSIEshBBtMj1fplDxSSej0QFni2//t8LS0hJKTwPQmY1mBW/8By2TNBnZf5jFyTfwA0Wu5G4rGWItuaLDaxcX8P2Q7o44M3PR+MnocC+6rt3UBq6DBw9iF2dZKjgYhrbmmujl/BuyiP0gZG6pCsB8zuaNS0srPq+UwtcSmJqLpnPTowymaZJK6CjNQiNaOb0epRTFsrviY7lS9DXdN3SQw9rmtVZ3de95yzEA0t37SZk2iZix5vyxWJ9p6FiGTia58YuY1C4sM0nE9VV/JyAaO4pZBgdHsqSTFsEa//nyg3BFFvdeIQWyEEK0QaniMTZTprPR2dO2HPHVChcuXiKR7QegK9P8QFUyYTK6/xDVwhQQzU7bbtDSA4ZLBZuzV3KkEhbJ2oGlhXw0ftLVEd90BnJdlIU8SxBGCyzK64yEKBWNdFwYy62YA/a8kIW8g2loZFMWX31xasXXFQp5YsluklYIaJjmzXfKeruiFyeeH1Ksrl8gzyxWef3yUmOTYblcJiAqQLo7VhZPjhvQmYm1vHv31tPHCbzoRcNIb/Tn5Adhy5Iy3mwScXNTBfJuiFvGqg2PfhDi+AHH93diGnpjFfaN/CDEMo2WHRC9lUiBLIQQLfad73yH/+1n/wExU2vk5VqmRmmDzmE7Xbx4mURmAIjiwJoVoqahc+L4sUaBPJ+LCtdWjYbML1U5dzVPJmWtGFMoVqPn77yJDOS6w4cOYpeiCLZ8ycWpbSK7URCEXJkscnWyiOcrCss6tK4fspi36e1M8N67h3jlwiKLtYUqAHOz08RSPWSTJrD5JSHLDQ1EawpLFZeq46/5lnau6HB1soiuacwuRtsFl2/RS8RNlgo2hbJLECocN2xZ/vFyHdk0vhNF6J06OghEs8nJm/zzEZGuTOyWvXeJuLnq97Fs+xwYzDZexMZiBmir03hsJ6CvK7GpVd+3GymQhRCixT772c/y27/xaV54/uuNj1mmvrsF8qXLJDL9JOI6pqmvGaV25x3HCNwyOn5t7EC1JMmiVPW4OF6gI22tmuG1Awv8MuomMpDrRkdHsYuzALUtgauTLFwv4MzVHPM5m65sjFTcYHq+suLz8zmbpZlLHOgqg4KvfW+68fmzb7xOPN1DT1cSTdO21K09OBoVmWPj06BommRRtX0ujEUvILJpi9mlKq4XMDU1Vduip0jGDEYHMwz2pqjYPgpFOtH6zqRl6lhEL5Due+thwlBt6pCZaG50MBMtArkFmYYGNywLUTfEBhp6NMazejyp9fPvtwopkIUQosUuXLgAwO/9t99qfMwydSq2vyOb6Zq5fPlyFPHWmVw3Z7W3O8vg0Ah4eeaW7GhZyBaTIZar2h660Xy+WOlpYrpzUxnIdYlEgkxt/HE+Z0ebyG643vmlKuWqR2cmhqZpWKZO2fap1kYYKlWPhVyVi2e+w7//lX/CW4718I2XpvFrJ/s/+zu/jWHGOXbkADFT31K37OSxAwBcuTZJs3Ebzw85dy2HZeo89Qf/lc/97hOAxkLeYWJikni6l3RCRzc0UgmL/YMZ7jnZx+mjPY0uXyuZpsbRgwPEtAr93SkcL4ii3/Zgp/DNrlnUm0bUWV4um7RWvbDTNBoLh/YaKZCFEKLFLly4CMCzX/x/mJmOYsPqhYW7xknwdrty5QqZ7lH6uhKgtDWzhlMJk9EDh6kWpphbqqLrWrRVb5uKFa9pOkW5XMJK9ZKOq5vOQK4bGR4gdIvMLFTRNA3XW3lQbz7vrOqy6rrGUiEao5hbquIFUC1M87U/e5b9nSUKZY/vnV3g29/+FmPz0fN1pOM3HfFWd8/p6NDbxPQCuk6jOK+bWazg+iExU+Pf/Mtf4rF//n+ihTaTc2XGJyaIZ/oaEW/1Dryha22ba7UMnY8/9H7+5f/7h9E0LSqQs3uzU/hmZxr6ivrYD0Isa3VaSzpl4S2LgwvDaHveXn1XQQpkIYRooSAIuHLlMj/4wI8SBAGfe/J3Gp9TKpoZ3Q1jY+OYqV4Ge1NNI97qLFPnwMHDLM1cZqHgoAOVbWYh+77PP/y5v8cbr76w6nNTtRXK3R2xm85Artu//wB2cZKZhSqmoVGuXC8+HTfAdoLV/9gnTGYWbcJQMTYbjVtU81N0dXXzR//tX9PbleCJPz7Lb3/J464P/iIAvZ3xLRcDx46O4lZzzOVcYqZOcdm4TRgqZhaqZBImL33veZYWF6iUS3zxmT/CD0IuXRkjkemnvzvNVg8J3izD0InFDGLL7luyDaMcYveZtU1/da4X0tFkbOLGg72uF5Ddw+8qSIEshBAtNDExgeu6vPu9P8D3vf9+Pve5J/kPv/8ab1xeQttGTu92+EHIQsFB0wyGe5OAWlH43OjE8eMszV4iDBWFitdIU9iqN86c5Q9//7/yib/9MS5futD4uFKK//57n0M3TPYNdt10BnLdwYMHyM1eZnqhEhXIy663bPuNLWbLmYaO5wcUKy4ztcNwCcvn43/n7/PVr/wp7zwScnJ/kkvf+SzD+iv8//7XdzDUl9pyBrBlGoT2HGUvjmUZlJYlWRQrHn4QYhg6X/ri57Esi/0HDvH7//13SMVNrl2bIJHpq0Wsbe2Q4FYkYgZ+EKKUQkO76YQRcXswdA3D0BrjX64fkE2tTiuJWTqo68Ww44V07OGtilIgCyFEC9Xnjw8dOsLHfupv0XnkR3j5/CLffWN+Vedwp8zOzaPHegAY6E1iaOtnDZ+64ziVfC3qreBsO+rt8uWrAJSKBf723/hJFhfmAfjVf/crfPdydB1ve+upm85Arjt48ADFhSvYbkDF9qk6fuN6F/M2MbN5YWcaOlPzFRZzDkophvuz/LWf/hm6unv44yf/DYtvPMnEK3/I3/2bf5m+rgShYssFsqFrJPQqyorSLHw/bMxzzi1VGy9YvvSnz/COd72Pj/3U3+LF7z7H+LULzM4vYVhJOrMxdE3bsQI5HosWSHh+SCphbunPRtweYpa+Ismi2Vx7zDIwTa3xOKWid2L2KvltF0KIFrp4MZo/PnzkKF2j97Lvzg+hVMjEbBnL0ilvkIHbDhcuXibVtQ+A3s7EqsM3N7rzjhPLot5sVLi9qLcrV6MC+Zf/3ePMzkzzdz/+Mf7Zv/ktXs2dZPDIe/iR9+3nyL7sljuUhw4dpLI0DhCNTajoeoNQsVRw1jxElEqaFMouCwUbr7LAgQMHMawkH//b/y/+7Mtf5Pee/C/82Id/koGBoegLlNpykahpGr0dBrphMTVXBC16K9vzQxYLNqmEydUrl7h44Sw/9MN/kR//yx/FNE1+//c+21ga0pmOEdvBec9k3CAIFI4X0JXdu51CEaXH1NdNK8Was/aZpIVXe2GnaWrD/5bczqRAFkKIFrpw4QKmaZHq6ON3v3CJpF5i4vXPMzFbahx484OdnUO+dOky6e5R0gkNy9h4VfDJk8dxK0toBMwv2Whsr0C+fPkqmqbxwF/4UX75V/4zft8PMeEeI67bPPrxe/mx9x8iDLnpDOS6I4cPU87VCuSFChAlWVTtqJOsrzEjqWsaSmnMLVYo5SYY3neIctXjY3/943R1deO5Ln/jZz7ReLyGVovE2prD+7oAePXMGKBhuz75koNGVEB/+U+fAeD7fuCDpLPd/OD9H+KpP3iSYqV+SNDa8iHBrUjETfwwxA8UmZTMH+9lMSvapuf5Icm4uea7FNmUheuH0drxJgf59pK9+5MJIcQuuHDhIiOjB/ns/3ORIAh55C+/hdL8JbxAMb9ko+/CRr2LFy+T6hplqDeFH4YkN4hlymQy9A8MovlFZpeqKLZXIF+9Nkb/wBAKnQulQwwe/T46g3P821/8MUYHswB4QXjTGch1Bw8exK0sohMwvVAFFWUhF8tuY1ELQLHi8unfe5WnvjbT+Fhn2mIhb1MtTLPvwCHSSQvTSvF//dNf5hN//3/n5B2nG49VqG0VBKdP7CcMfM5fncUyosUx0/OVxuGnZ//089zxlvv4zWfm+NXffZWP/C9/ncWFecLaivBsKrajBXJUJGltWWUtbi3JRDRO43oBHeu8GEomTEJV2+C4x7cqym+8EEK00IULFzh4149w7lqen/5LJ7jj+CBd6Whmb2KuzOF9WRwvJJ3cuWu6fOUK6e4fZN9gB0G4ubdFDx8+gl2cYW5pGE1jW0X9xPgYw6OH+PTnXuP81Tx/9UPH+P63ff+Kx2wlA7mup6eHnt4+ND/H9EJv46Berug0CsqxmRL/8fdfZ7HgoGvwV0ounZkYjhdgu4pqfor9B6JZ47GZEn/pwb+y+htpbGsO9+TJ41T+4AtMpXqJWQZLRRfPC+nKxsjllnjhu9/hL3z8PzOfs5nP2fz4B+5jcGiEeKYXUKSS5o5mzlqmThgo4jF9R0c7xM4zDQOFwvNZd/FH/d0nP1B7+oAeSAdZCCFaRinFpcuXyPQdpyNt8e67otXOxw8OolTI+EwJU9/ZOWSlFGMTc5ixNEO9SVBs6pDX0aNHyc9dYT5nYxjalqPeXC9ganqKvrv+Fheu5Xn4x07y/W8bbnKdW8tArjt58hTlpXFmFiqYpk6+6FC1A2KWwXffmOOX/8tLKKX4mz92klDB869H66nnl6Is5GphitH9h+jpjBMzjVUd8zBUGLq+pS16dcPDw1Tz4xRsE9OIEk302h/Fn335ixx77yNUVRd//UeOk06afPm70/zERz5GIt1LwgLD0LDWOHDYDqahESpFp8wf73mWGSVUNFsQslwUc6gI1d6ePwYpkIUQomXm5+cpFYuYqT4Ge1ONfNC33HUXlfwkl8cXo5XTO1gge37IQiH6fkO9KahtktvIsWPHWJi+gB8oyhWPir21DrLjBpQdAxUf5CM/fIR3vWWg+QO3mIFcd+rOO5mbOMNS0SUIQmw3BBRj0yV+46kzHBjK8Hd//BBfeupTpPQS33o1GrOYXaoCkDR9UukMMdNguD+1IioOIAjX3j64WYmYgUWRQEtSsX0MQyNdW/TxxW+NMXLHA3zoPaO89+4hvv9tw7x8boEf+fGH2X/0Lvq6UwA7OvNpGjqWqdOxx99KF9GLL2obp9cb49F1jVStMN7u34dbnRTIQgjRIvWIN1elom5tzem77qa8cJWx6SKWpVOpeNuKTdtIuepRtX2CMEogqHjRP2iDvSlQmyuyjh8/1kiyWCo6VJZFp92MqZlZYpkRAO441L3m47aagVx35513sjQTJYjM52yqjk/MMnjp/AKaBp32t/krP/Iufus3Ps3r3/p9xmfKjM+Wo/XUwEBPmkTMQNc1ejrioNSKnzcIQhLbHDMwTYOu2q/FxFyZrkwcQ9e4PL6E33EfMW+cH/uBQwD8wNuH0XSNl6+4DIwco68rxU4tCanTdY1syiIlC0L2PMvUo9/xuLHhGFE2HSObim3r3ZTbgRTIQgjRIhcvXsRKZPECjcGeVOPjp+68i/LSVUqOhuuFBGp7h97WopRiar7CqxcWeeXCAt99Y5bvvXYNM9mHTkBnxkLT2VQSw8kTx6nml0W9bfKaqzcsQjl//jLp3oPommKgp/ngdRiqLWcg173l9GkqjSSLKh1pi2Tc4OVzc9i5q/zrf/6PuOvut/Pz//ifMvbGF9E1xbdfmWFuycaz8+zfv6/RGYtZBn1dyRULUvxARYsStsHQNfYNRAfuxqaLjY//0bOvEoY+H3pHZyNxoysb575TfXzjpRkW83ZtzfTOLQmpOzCc3fBQp7j9GXqUr72ZdwuyKYvuN8HYjRTIQgjRIufOXyDdtR+AwWUd5FQqTSbmARpTc2VQiqrT2iSLMFRcmy5xdapIZyZGVzZOZzrG9OQYqa5ROpIqilKLGZtaDXvs2DHs8gIaIXNLNvXotPVMzVd46dwC87WxBYBLl6+S6TlET9ZYs+PkB+G2t7TdffddVAvTgGJ6IUqGKFU9xmYrTJz7c/7Vr/xHPvNf/oCf+um/jaUHmO4kz702y+RckXJukn0HDpNcFjM30JPE9QJcL6Bc9ag4/rYPyFmmzv79+3Crec5fmQWiFx3nJz3mr3yL7/++71vx+B96xz5sN8DxQro6dnZJSF0qYe7ZVcLiOk3TSMQMspsokLs74tG7UXucFMhCCNEi58+fZ/DAW4DavO8yh2oZuBNzFQxDo1RxW/Z9g1BxcSLP9HyF7mysEW2maRqz0xOkuvYx0JPA80PSyc0drOnp6aGjI4sWlJlbuh6d1oxSivHZElcni2RTFhfHCxTLblS0j42R6TnI/sHM2tcfqC1nINcNDQ7Q1dWFHpSYXohWR79xKQdolGZf4y/92F9B0zTiiQTved8PcO75pyiUPS5PlqkWptg3enhFlFk6adLdEUfXdXo7E9xxqKvWxd26eMzg4KEjlBYuMzZTAuDVi4sEWMS9a2SyHSsef3A4y9HR6GM7vSREvPl0ZmKberdA07QV8Yl7lRTIQgjRIhcvXqJv5DiWqUdzrDXFisuRw4fw3Qrnr84StwxyxdYVyMWyy/ySQ3dHfFW379rYGMnsIAdGuvH8kExy8/Okhw8fxSvPMbdkN6LTbqRU1Lkeny7R1RHDMnXSSZOzV3MUyi4TU7PE070c2d+75vfZTgbycsdPnKRamIyykIHXLi0SemWO7OvENK8//w984Ie5/OqzxGu3olqYZv+BwytmszVN48TBbu480s2B4Sx9XcltF6iGrnH06FFKi1fIlaOu/9e/N4lTXuCeU4NNv+aH31XfgBjf0Qxk8eYTjdPs7WSKmyEFshDithaGascXb6zl8qWLpLpHGehONDosrhegoXHnW+6mvHSNy2P///buO0zOsmr8+Pd5nulle8+mbEu2ZNMLvQgBRIoCIthQ1Pja0FdUeEXE8r6CWH82FETFiqACShUivZNeSG/be5k+T/v9Mcmwy+4mu5vNbgLnc114mZl7nrnnTnbnzD3nPidVySISM9KtXY9UJKbjcg6/o7OvuQeAWdNysQH3GALR8vIK+rr20dETS5V6G6b6RndfnOaOSGq39UBw7nJqODWV3U39dPQkANK5twNZtk1vOImmqmQe4e4sQE1NLV3N2+joiWGaFpt399C5fzXzFiweNO6kk0/H4VBxJvYDEOtrYcbMsiOqojFas2ZOIxlqwbJVdjX1s2V3L63bn+SEE04ZdvyC2Xl867+WUJLvlwBZiEkkAbIQ4rgWjunsH3DgaaqEQiE6OzvQ3Lnp/DzLtgnHDCqmZ1JfX0+4ey/doYNB8cTlIfdHdVwj1MftOFDntyjXB/bYDppVVlbQ1bKDhG4RT5jD7iD3RZLD5jV7PQ4UBUKJ1PO9OUCOJ036QkmKcn3UV+Xg8xz5zlVdXR297bsxTJs1WzuJxAw69r7KgoVLB43zBwKceNJpbHr+TyhmFJfdi9vrnZQawxl+FwF36oPG/U/uxUahbedTLF5ywoiPyc/2YphHXmZOCDF6EiALIY5roUiS/sjk1RUeya5du1BUB0nbnS7xFookKcn3kxlwkZ+XjUeNYeKkL5xEUZUJaRhi26k6xSPtfobiKrZtHaggoeAaQx3dqqpKIr3NAHT1xdENa8iud39YHzFw83uc6ARQrPig0/GRmI5l2dRV5DCjKDBhB8/mzq0j2tsEwKpXmwCb7sa1zFs4eAfZtGzOOe9Cdm95kTX/+AxFean6x5NRtsrjclCUG8C2THY39WNGmimbnjck/zj6pg8jNrbkIAsxiSRAFkIc13r6E+i6eVTKpo3Fjh078WYUA6kSb7G4gcftSO+cBn3O9MG9xvYIbodKb/jI85ATupkqkzZCpQEdPw47hqqAy6mOqZTawFJvHT1xFBhUyeJglYeRAlzDMFA9BXi1N6pahGM6mqZSW55NwDex9XXn1c9Nl3rb1xJGSXaSn5tBYWGqc59t2/SFk4SiOqeeeS6qqtLT3cX0GWWTVsrM7dIonT6daF8qkN+z/kGWnXDyoDF94SS6YREfWDLPHl2DFyHExJCfNiHEccswLSJxA01VR6ywMFm2b9+JP7sUSJV4i+smZdMy0ruSHreD2eWpA1fbdrficmnpSg9HIpG0GOkK/X19OAOFBNypDxBjTWOorKwkHm5HwU51nFMUksYb6xxPmqRafAyvrbUFf/YMcgKpMf2RJC6HRvWsrKOyGzqtpIiA34NipQLyjr2vMn9BKr3Csmx6Qklys9wU5fnwBrJZtGQ5AKUzyibtcJLToTJzVjmhzt0o2DRvf4rlA/KPw1Edn9dBeWnG4BQc5UC3MyHEpJAAWQhx3IrGDRQUbOXwNXqPtu07dpBTXAWkOtYpKINq+3pcGnPn1hEPdbB9dyuqokzIAcNo3KBh705isVRpM9u20806Xn7xOXyZJeRnudDN0Zd4O6i4uBi3y4VmRWjtiqIA8QFBWyRmcKgSudt2N6E53ZTk+4nFDbxuB3OOUnB8UNXsapLhVBvpvZufZP7CxeiGRW84ycziIGUlGWQGXFiWzYpzLgCgpHQW3gnIgR4NRVGoqqpiz2t/pnfLH7D0aDr/OJE0QVGoLM0kO+jG5dQGfDNiyw6yEJNI6nkIIY5bkaiOqgIoB76OPvJKCOO1c+dOcovOJivowqkpWG9KZ3A5Vapr6gn/5be0ZdQCqWApGtePKDjbvaeBK99zBnn5BXz22m+yJ1rJnqYQTiVBW8MuckoXMq+2BNOy8Y6xZbCiKJSVlZOMtNPWVZCqvhF/I2+6P5zAPSD3ubu7C0M3KChMlSzbvb8TyKRqVj4Jw2Raof+oB3lzqqtZvXszZfNn0N+xg/kLlxCJ61SUBsnPTqW4uJ0aQZ+Td174Xnbv2s7S5adOan5vbe0cYv2trH72b9TPX0QgmIFhWsQSBrUVOemc7mkFPva2hMj0u1AU5S3f2leIY4l8HBVCHLe6+xN4XFq6bNpU2r1nN77MaRTm+oZNZ1AUhbzcLBxWH3HLQ1I3cTpU+iLjz0O2bZt1GzZgGAauQAEPvmaxu6GbZPtLNGx/idyiclxOlbmziwDG1Sq5rKKC/gOl3lRVSa+zbduEojquA8Hc/qY2vvjdh7nuh48TiqQqZzR3RLEtk7rZqe6CngmodXw4c+vq2PbCb9Ba/oHToVFbNw9shczA4A9PhTle3P4MvnXzjwkEM8Z0ePFIlc0oxetNBesH849DUYOyaRmD6lRnZ3hQUNANC7dzdB0QhRATQwJkIcRxyTAtIjEDp0MdsrM52Xr7QrQ2N4Irm6Ic74jpDAGvg/wMBUXR2NsSwu1Uj6hhiG5Y7NqxjYzCaua983/JzC5g19PfZ/WjP+aD55Xx86+9ix9fexLFeX6wFdzj2CWtrKykvWELhmnTF04QS5jYtk08aWJZoCoKnT1R/u+Ol3AFinFllPLdXz+Nadn0RCAeaiM7OwtsZVwB+ljNravDMnUef+heqmvr0RxuvB5tyA5xRsCdSs+xbVCYlBrIB3ncDkpnlAGw/IRTsGwbVUm18B3I6VApzPWlS+kJISaPBMhCiONSLG5gY6MoCg5NJaGbmEd44G28Nm7eisuXjYWDwlzviOkMAZ+Typn5qcdsa0HTVHTDGncecjxpsnv3Hha+61v4fS6+9onl/POBv/HEM2u59PIPoCgKyoFcZ01lXOkNVZWpHWSA9u442Kl871Qusk1bV5Rv/vJ5LNwsndFNeM/DdEV93P3YDuKWDzvRmXp+TZmUNIZ58+oBiMdjLFi4hFjCIC/TM2Sc06GSneEmEksd8pyoUnOj4XaqlM4oQ1VVFi85gWjMIC/LM+wc8rM9YCM1kIWYZBIgCyGOS+GojqYqmJad2gVEmbJKFps2bcaXmapQcbCU23C7pS6XRnX1bMLd+3h9V8eBW5X0obqxisUNmjoiaE4PV55bSUGOF6/XR15+waBxhmmNOf/4oNlVVenawm1dUQ6ucyiSJJE0ueW3rxKNxclJvsAnrrqcj1/5Dvat/wfPrWsDZyZuNULSsAiM8YDgeJUUF5KZlQPAvAWLsSyb4IAazAPlZ3uJHjg8OJk0TeX9H/wY1173DQLBDHTTIi9raBAP4HU7yM/2yg6yEJNMAmQhxHGpJ5TEoSrc8PNXeGZtC9j2lNVC3rT5dfzZqTzbVBe94RtyuJ0alVU19LVuobXXwrJsnJpCKDq69JA375D3R5L0x1KB04yiwIiP042xV7A4qKqqEiMRwqmatHbFQIGkYdEXSbJxWzNxXSW8416+9fWvAnDGO87FE1lPqHUdANk+G90wJ7zm8Ug0TaWyag4A8xYsQVGUEQ9BBnxOvG4N3yTVQB7oHWedyfuv+hSGaeFyaPi9I6/PjOIAWRPQilsIMXpHLUCOx+MsW7aM+fPnU1dXx0033QRAd3c3K1asoKqqihUrVtDT05N+zM0330xlZSVz5szhscceO1pTE0Ic50zTIhzVaeqI0BdOsruxH0VVjrhk2rjmYtns2LGdgtJqXE6VjIATRRk+ncHpUCkoLMQMN2HaGs2dUVxOldAoOgHGkwa7GvoIDwimGxpbcAZKcKnJQwZYujn2GsgHzZgxA5/PD3ovbd1RHKpCOKoTi5us3bwHU49z3bWfxe1J7YAqisLnvvAVVj/0v7z+1E+ZUeDAtGx849zBHo/FS5ZRMm0GBYXTyc5wj1j9QVMVCnJ8+CZpd3uggNeJfqCOd1GuF/UQFSo8LoekWAgxyY5agOx2u/nPf/7D+vXrWbduHY8++igvvfQSt9xyC2eddRY7duzgrLPO4pZbbgFgy5Yt3H333WzevJlHH32UT3/605jm1Bb+F0Ice5588kkuvfQyorEwOxv6AWjriuFQlSHteSdDPGGwb89OMgvKKczxYpk2PrdjxIoDAa+TvGBqJ3hXYx8Oh0o0rh9IExlZV2+cRNJk694eonED3bDYvu11ArnlFGYdOsBTUMYdYGmaRt3cekJd+2jtiuFwqPSFEoBNc2eCcNcu5tbPH/SYM95xLjU1tbRse5xpJdPgCJ5/PL524zf4w71PkDQtcobJPx6oJN9HbpZ3kmb2Bo/bAXaqgUlWhuwOC3GsOWoBsqIoBAKpr/x0XUfXdRRF4YEHHuCqq64C4KqrruL+++8H4IEHHuCKK67A7XZTVlZGZWUlr7zyytGanhDiOPXXv/6VBx64j+98/Yts398HQGt3DIemTEmpt0gsyb69u3D6CtIl3vyH2K0N+pyUzSohEelm5/4+VEXBtlMto0diWjatXTECfhcup8bWPT30hhLs2LUTX1YJFTNzDzvPI6kgsXDhIlr3byYc1UnqJgnDxrAsYpYfTe/C5R4c4CmKwue/+D8AVM6uTh0ym8QqERlBL4GMTLCVQ/5dQColYyrqC7sPNAEJ+pyTngMthDi8o/pTaZomixcvZufOnXzmM59h+fLltLW1UVxcDKS6NLW3twPQ1NTECSeckH5saWkpTU1NQ655++23c/vttwPQ2tpKc3Pz0XwJx62Ojo7DDxKHJes4MSZyHV977TVcLhdP/PtBrJkfwe10kkiaNLW04tQUMt3RSa0X+9r67aD5MBUvhZnQ1dmOS/HS3Bwednw4plNcUsqG1zazdU8O3Z1t9Ed19jfEBtXAHSgU0enqDGEnQ2hKquPahu52tu1oQMmuoTTPQ3dn27CPtQ88Z1eHPu51qaqs5O+PpDYsdu9txu9V6Q3pKKqDHL857HPX18/n4cdfICMzm1i4k7a2yfvwkkiadHf24vU46Ooc+rzHws+1bdvEI70oHh/NzfGpns64HAvr+FYg6zgxJnodj2qArGka69ato7e3l/e85z1s2rRpxLHDfb043C/zlStXsnLlSgCWLFlCSUnJxE34LUbWZmLIOk6MiVhHy7LYvn07F1/6Qbr6LWw0ygvh9UZI2gFyMn3kF+ROale0hkeeI6OwGoC5s6eREXRROi2bzMDwlRNiCYN5C5dzz4M/IVxxKriyyPEqBDMDFOf5hn3Mlt3dFBX6iYac5OQVpq/TG1VxZ0PdnOkjHuLSDQt/hs20aYffZR7J2SvO5uvf/h4AUdNDVXEuW/buBKC+ujQ9pzfLySskFjfw+5yUlGSO+/nHyjQt2kIuZhT6KSkY/vDisfBz7fJlk50xfHm348WxsI5vBbKOE2Mi13FSfiqzsrI444wzePTRRyksLKSlpQWAlpYWCgpS5YhKS0tpaGhIP6axsVH+wQghBtm3bx+hUIiK2bWcd9mnAfjn778BHChBptgkJ7iShWFaI5aPSyRNdu/cQWZhNQ5NobTQD8qhG2K4nRplFVX0t20FUnnILodKaISOerG4QSiqp3JWB/C6HUR0D4oVHxKMxxMGiaSJZdsYw3T1G6u62howQmBbtHXF8HudbNnZSiLSxYJ5NYd8bNKwyPBP3gE9SKVNBP1OMgLHdm5vfrbvuA6OhXgrO2o/mR0dHfT29gIQi8V44oknqK6u5qKLLuKuu+4C4K677uLiiy8G4KKLLuLuu+8mkUiwZ88eduzYwbJly47W9IQQo6Ab1qCqCVNt48aNAFTOrmF/W4KcoErLnnUoGKkSZEBSn9gAuac/wcYdXcMeAIwnDfbu2UFOSR2zioMHgh37kDvYqqqQnRkkN0MFK8muhn6cTo1wbPh17uyND5sj29vbgzNQQtCdHPRtW184iaIqOJwq4ahONGEcssLFaDidDqpr6jDjXbQdWOfWbp2+9m1U18wdNPbNHyZs2x4S3E+GmcXBI/5gIIR4+zpqvz1aWlq46qqrME0Ty7K4/PLLueCCCzjxxBO5/PLLufPOO5kxYwb33nsvAHV1dVx++eXU1tbicDj4+c9/jqZJWRshpopp2exu7COWNFkwO2+qpwPAhg0bAKiqqubvL21l+dxCXq+ZixnrpK07D01ViMV1mMCqAAcrRmzZ3U11WXY6Tzgc1dnfGqZh/z4Cc99NeWkGhmnhdmqHPfSV4XdRUVlNuHs3uxqz0VQFw7BJ6uag4No0Ldq6h89N3r59K/7s6UxLNebDtm16Q0nysjzMKgmiaSq2bZPQTZwTsEs5b/4C1jXvobVrRuqwnu1F07sIBILpMX3hJCgK8aRJxoDmHONpcX2kRsrnFkKI0ThqAfK8efNYu3btkNtzc3NZtWrVsI+54YYbuOGGG47WlIQQo2TbNg2tIfrCSWxSqQTHQh3WjRs3Ujp9FuGkRiJpMntGJvXzFvJ66y5aC2fi1NQJr2QxcAd2y+5uKqdn0dMfp6Mnjtet0dFrEFQ1yqdlYBgW/lHU+83wuyivrObfL67Gn19NLG6k0kN0a1CA3BdOYlr2sDVyN27Zi6qVUl2Rh2WlguOSAj+lBf70eEVR8Lgm5tf84sWLeXbTs3T0xNjVmCqvV5yTurZt2/SFk2RnuplRGGTbvl6icQOPW0NVD51yIoQQxyL5rSWEGKK1K0ZrV4zMgAuFqakvPJz1GzZQUVXD7gMBWuX0TObOW0hfxx56+hPYtj3hc43FDRwOFbdLw+d2sH1fL72hBNlBF2YyiuVKbeGWTQuimxZez+E/SHg9GpWza+lrex3bhj3NodRzvanldGtXFO8IXd52N6aaLM2rmUEkrlOc72NGUeCQDSeOxNKlS4j2NGLZ8ML6JmzLpKayGNu26Qklycv2UD4tE7dLY/bMTEzLJhLT8Xmck1pVRAghJoIEyEKINMuy6eqNsa8lRFbAhaIoOB3KgcYQUysej7Nj+3YqqmrYsb+PolwvmQEX9fULifSlSkJ29iVI6OaQlszjZZgWhmmlUyZcTo2cDDdBX2pt9uzZRWZhNX5XKqXAtGy8o9hBdjs1ZtfU0t++A4D9rWGcmjoo3zuWOHA4z6URDof43E2/5zu/fALTTOVYd/RZWEacghwfpsmIVTMmytzaWox4JwCbdvUS7t7HvPp6QlGdwhwvs4oz0uvkcTmYMzOLpG4RmIIudUIIcaQkQBZCkNRNWjqjrN/exc7GfoI+Z3on0uPS6A4lDtvp7WjbsmULlmVRMbuWnY39VM1IlQ0rnl6BEU3VU2/tiqIAyQlqOa3rVqqQ8Ah27dxORmE1M4v96dtGk06gKAo1sytxO1U0O0JjexiXUyM0IEDu7U+gqgqtLU1c9ZGrMTxlRLQZfOXmP2NZFgkCOKxUoxEUjnoKjMfjZFphFgCWrdDfvp2aunmYlk1elmfIznXA56SmLJucrEN3shNCiGORBMhCvM0ldZONO7tpbAvjdqlkB904HW/8atA0FcOwDtnpbTIcrGCRXzKbeMKkanoqQLYVlenFudi2naqwoCgjVoQYq6RhwiHSA7btasDty6auqogDk8HlGN2v1ZxMDxVVNST6Gmloi+B0qMQTJqZppV5Ld4z9u7bw3nevwA7WoCo23uQuotpMrv3Wb3AHp5ETsA98cLGP+kE4h6ZSU1NNMppK7VCS7WRn56DAiFUqsoJuOSwnhDguSYAsxNtcOGZgmjaZAdfINVkViManNkBev349breHOKnA+OAOMjbUzZ1HItxOS2cEj1Olq29iOpMldZNDZc82tEYBmD0jG8u20VQGfbg4FJ/HScXsGtobNtHRHSOeNEGBhJ4qrbdzx3Y+fMUFOFxepteuYGldIV/91LkErP3E3XPQnB5mlWQeaG3tPGq5xwMtmL+QSG8jACW5bnTDwu3SRv2ahRDieCG/1YR4m+vuix82LcCpqfSGprYd7oYNGymrmMP+1gi5WR6ygm5M08LhUFm8aDHhngYaWnpxuzT6wzqGeeT1kKNxE4c2cuDZl3BjW0lK8v0kdQu/b/QH0jwujarZtXQ0bcEGmtsjgE08adLVF+e1l58hGo3w+Zt+S9KAUxcWo6oqt1x/JT4r1WxpybwKkrpF0Dc5u7SLlywh3LWHZKyP2qrpJHXzqOc+CyHEVJAAWYi3MdOy6elP4BmhUsJBHreDnlBySvOQN27cSOXsGnY39VNWkqq9G0+aZAfdLFu+lGhvI139+oGUYXtCyr1FYgbWCAf+TNMETzFeNYSqKiSSJplj6Nymqgr19fWEO/cA0NAexqGq9IeTdPTE2b93J8FgBlv2G0zL91E+LfWaNU3l1usv43OXVTK/rgLDsgj4JydInV9fS/Omf/DafV+irn4eumkNqncshBBvFRIgC/E2FonpWLadOuj1Jn19vXziE5/g3489gqYqmGZqd3MqtLe3097exqyq+fSGkulgUTctMoNuamuqMWNdWLZKb38Ch6bSOwGVNxrawlz305e5/6k9Qz4c7NmzF3/2DIqyUx8ubBv8Y6zYsHTJQhKRTjTFoLEtgsuZmrdlw64dW5mz4Ewa2iKcurB40M60pqnUVhUf+JOCZ5JqVHs9LirKK4iH2qitm4dtj5x/LIQQxzP5zSbE21hfKDlsCkEykeDz134Nd9kH+NczmznnXFBIBdTeKQiIDh7Qyymuhn4oK8lI3WGDz6Nhmir5OV4A2rpjzJ6RSVdfnBlFgXHX4DVMi8a2MLYNj73YSDSmU5ndzpZNG9i9Zyd7uwL4Z65gzqxcDk5mrGszrSiP4mnTsWPtNLZl43Co9PTHyQw42blzG8svuhycKsvmFox4DQVwT1IjDpdTZckJp9LX20VBYTH9B8rQCSHEW43sIAvxNmXbNp29cXxvCups2+b6r96Ao/RdqKpGxMoGwOVQ6Q0lp2KqrFuXajFtu/JwaAqlhX5My0418HBquJwalTNTO6pNbaF05Y14Yvw73kndorM3lXethrbw7Lo2vvPLJ/jFr//E3uQC/DNX4DQ7OfvURQcOqznGfFjN63Ewu7qenrbtNHVEsG3IDDiJhnvpD8XQXTNZWlcwYuCtGxYet4Y2Aa2kR8PpUPnEp7/EA488i27YBLyuSTkcKIQQk00CZCHepmIJE90whwRX3//+rXQ7l+H1uMh2tOMKTqO9oxu3S6MvlBgxJ/doWrtuHTm5+bR0m8woCuLQVOIJg6zgwWYmKvVza9ETYbbtbk49SIFQdPwBvW6Y7NzTRCLSxYZV/w9vfDPFc85i8cW3UDJjDh+9cA7/74Z3E/B7SOomWcGx5+I6NJW6unqadq9FNyzau2N43A527dxGYeVpWKicsqBoxMcndZPgJJZRUxSFgNeFw+khoZtkBaSEmxDirUkCZCHepvojSd5cw+zRhx9kTUMW3owC/vtDS1k4OxNFUXn6pS2oqoJhTU0e8oYNG6iaU8f+1tCg/OOsAYfiFi9ZSrS3icbWPgC8LgedfePPQ44nTNq7IkT7Wrjnvn/zw2/+Fx86v4qLTpvJNz65hGVzC9LpG7ppERznYbVFixcS6twNQGNbGICdO7ZRNPsdFGQ7mVEUGPGxumkT8E9ukOrzOtANC9Oy8U9S9QwhhJhsEiAL8TbVNSC9oqsvzgNP7+X+1Q6yimv56EXVlE/L4LQT6jH1BJt3dQCpnhnhI9iVHY9IJMKWLZuoqj8Vw7QpOxAgKyh4PW+kHlRVlmFEO+iLpf7scqqEo0l0Y3zl3mJxg0hSxYx1UlQ8DYCT5hfxzpNnDJN3q+A9TCWQkZywbDHR3kYULBrbIwC8vrORzMI5nLqwdFAOtTlk896e9ENyfo8zvaYelxxjEUK8NUmALMTbUFI3icR0XE6Nv6/azY2/eJXHXmigu/l1Cu3VLJub+lq/sLCQWM8u2vtTwZ/nCHdlx+P5F17GNAwKZ84HUgf0TMtG1QZXb/B7nQQ9Brbqo6svjqIo2DZE4+PrqtfZF8dWPWT4lEMe9LMsG01h3IfVymbNJBjMQDX7aDiwg9zc58O2rUGH85K6SSiSJBYfXL5usg/JedxaOv97NG21hRDieCS/3YR4GwofqBEcien859Um5s/O5fTKNtY/8i0uPvekQWMDjhC2M5v+SBK3UyUcmZgmHKP15FPPAGC58skKusjOcJNImmQFXIMCV7dLo6zYB8Ca11uBVIOTvnEcLLRtm/0t/QCUFAQPOTapmwT9rnFXy/C4HMyuriPctYeGtkgqxzs4G6feOqjGcDRuUJznwzyQ5mKYFm6nNnL3w6PE5dAwDItM3/hfsxBCHOskQBbibairJ4bbqbFldw+WDStOKOW5Vf+koLCY+QuXDBpbXuIHYOP21gMB0cQ04Rit555/joqqahrb45RPS5V3SxqpAHkgl1Nl0fxaYv2tvLKhIX1beBxzNUybrTv2A1BVVnLIsQnDOqJucqqqUDd3Pi271xGO6jz5yh6c3mxm5LyxU29ZNoqikJPpobos+8A3AAaBKcgBdjlVnE6VDDmgJ4R4C5MAWYi3GdO06A0ncbs1NuzsJuhzUpit8cxTT7Di3HehqoN/LSyZX4GRjPLqhn0AE9aEYzQSSZ11a15l0bLT6epLpDvogYLPMzhAczk05s5fRNf+1TR1mehGqg11NK6PuQNgUjfZvS/Vznlh/ZxDjrVtG/8RVpJYsGA+PW3bAXj4hSb0RJjFtW9Ur4jEdQpyvGiqgs/joHpWNoZpkTHJB/Qg1aQk4HMOWX8hhHgrkQBZiEnU059gX0uIvU397Gnqo6UjMqnpCpBKr7BtsC2bzbu6qa/M4fln/kM8HmPFeRcOGV9fv4Dels3sa0sFxV63Rk9/YsLaTpumRSKZyokORwfnC7+2ZgPhUD8zZp8AQNm04IHOf6mUioFUVaEgPw+n0YqNxo79faiKgmXZJPWxrbFuWLR1RYiHO5hTXX3IsaluckeWB7x0yWLC3XsBiCagbeczzJnzxvMahk1+tjf954DPSX1V7phaW0+k0oLAoAOSQgjxViMBshCTqLkjQkdPjJ5Qgr6wTmN7hI07uukLT97Bt95QAoemsKOhn1jCZF5VLv9+9F9kZeewdNlJQ8bn5RdghPYSN9309CfQNJWkbk1IubfeUILXXu9gw44utuzqYdOublo6o+n7n3zyaQA82WVoqsL0wgBJ3SLocw7boMLncVA1PRPLSLJpZxeQqt2b0Ec3V8uyCUWSdPbGCccV0PvQHM4RK2HohoXP4zjiPOC62mo0TBx26rX37n+B4pJSAOJJk6Dfie9NAWnA68TlnJoudpkBF5o0CBFCvIVJgCzEJLEsm2jcIOhz4vemAp7MgAunQ+H1PT3sbOjFPMq7yZZl09kXx+txsHFnFw5NobzEy5OrHuWsFefjcAwOwkzTIpYwKMpM7RZv39ebvu/Nu73j0dOfwOVQyQy4yAy6yAq42NccorMnhm3bvPDCCxQUFtHZD6WFflxOjaRukjHCzqnf66R+/kK6mzewblt76kYF4omhechJ3aS7P0FHT4yWjgh7mvpZu62T1/f00B9OYjmCBD02oWiSSMwY9gNBImmSOc76xwMF/R4qqmqI9+7GirdTkKWlU11iCZOiXN8RP4cQQojRkwBZiEmSNFIB1ptP/rucGtlBN129CSLxo3v4LZYwMI1UisL6Hd1Uz8pmzavPEw6FOOe8CwaNtWybvkiSeNKkdvZ09Hg/m3d1AuBxqXT3H/mud184OahMmaoqZAac7Grsp607xtrVL7Nw6SnsaQ5RWZqZmpcFfu/wX+973Rpz5y+ha/9qesIm7d0xnJpKODY0mG/pjLJtbw97m0M0dUToDSXwexxkBd30dHfhcPkpyvODDTOKAuhG6sNCei3jBrphkRk88jQHTVOprp3LxlU/5vXHv01lZSrv2bRsNFU5okOAQgghxk4CZCEmSSJpjZi3qygKqqoMqXE70frDSRQ1FRx29caZV5XD4489iD8Q5KSTzxg0ti+cpLQggM/joKZuHj3Nm9iypxvbtnG7NPrDySPa8U4kTZKGNaTV9cFDYK+s2UprSyMVdWdgmDZ1FdkAKIo9Yu1fp0Nl5sxKkj2pA2+bdnXjdKiEo0PXtTeUIMPvIjPgIsPvwu99I21j9frXAaicVQyKQmbQRW1ZNqaVal/dE0rgcKrUVeZMWPA6f/58erraaWveR0VVKkCOxHSK8rxD1kgIIcTRJb91hZgk8YSR3j1OxON89IPv4ZGH7k/f73KohCYgbeFQ2ntS3fM27uwGYFahg0ceuo93nH0eLvcbO6G94SR5mR5K8v3kZLipmD2Xnqb1ROLQ0ZNqwmHZqZSR8YolUocFh+N0qGzbsib1/7MqcDpUKqdnYpgWLqc2Yu6ty6mhagq1c2ahR9rSAXI8aWBabzxZUjdJJC2cjtSvwK9d/3m+f8s30vdv29UEwIL6KrBTfzdej4Pa8iyCXhdV0zOpLcsmcITVKwZasnhR+v9XHgiQLQtyMzwT9hxCCCFGR44hCzFJQlEd14GA7K7f3MYLzz1FMJjBO9/1bgCcTpXIMKkAEyWeNEgkDbxBNxt2dDGzKMB9d/+acCjExz95DZAqWRaK6vi9DmaVBFFVhaDfRXZOAcQaAdi8u5uCnGk4NIXecJLgOHNw+8NJnNrIB73Wr3kZn89Pa6/GnJkBnI7U+mQfIqXB6VBRVZUFi5bx0PMv4gkWkUiaYEMyaaYrL6RSJVIB8/PPPsm9d/8egJmzynnvFR+mqa0P228xs7QAfcAut8flYPasrHG93sNZuGD+ge5/NlWza0jqJj6PJtUihBBiCsgOshCTJBLTcTpV2ttbue3nPwRg/brX0vc7NJVE0pqwsm+maRGLG6nObEAoogMK/ZEke5pCVE33cddvb+Oc8y6kcnYtveEkfeEkmYHUDunBoNDncYBiM6eiFD3SwZbdPQB43Q66euPjLvfWG04OKdU20OpXX2LhCSvo6I1TV54DgG5aZBwmpcHvdVA3bzFdDa9hWjbb9/cBgytZ9Ed0NE3Bsiy+f8s3mFY6g5NOOYNvff0rbNq4jr6IBXoI2wb/JAWoeblZlM4ow+PxUjJtOtGEQaEczhNCiCkhAbIQkyBV69fCoan86Hv/i55M8IEPf5zWlmba2lrS4xRSublHqquri7q6uSxasoTzL7yUz37+Oh57/Gk8bo1Nu7qxgV3rHiMcCvHJz36JcNRgemGABXPyqJqRNSiFwaGp+D1OaucuoG3Py2zb15tqwnEE5d50wyKe0Hl61SPEYtEh94f6+9i+bQsza88AoLY8lX+cqjl86IA1O+hmds0Cwh07AWhoDaOqDMrv7g0l8LgcPPLgfWzZvIHPX/tVfvCTX5Obl8c1//VhTC2I321iGBbewzzfRHE5NZafeBqLlixPV7CQw3lCCDE1JEAWYhIkDjSq2LRxHff97c986KOf5MKL3wvAxvVr0+NsxU6PPRIvvvQy27a9jlNT2bRhNbf97PtcdeW7eOBvf2DDjm4yA07uuesHnHPehcwoq6akwEdxnm/E3N6cDDfzF51I1/7V6IbNzoa+1B0KhCLJMc8vGjd4ffMGPvPJD/Lfn/sYpjk4yH7s0X9hWRZasIz8bA8FOV5s20ZVlBEP6B0U9LvweH1UVVViJXtp6ogMyu8+WI3Ctgx+9P3/pbpmLhde/F5ycnL5fz//He3trXgziinM8WJYFr4RKmYcDf978w/5xa/vIZYwyQ66p6zOsRBCvN1JgCzEJIgnTWIJne/99A9ULLqYRWd8lG6jkED2NDauX50e51AnJg953fpNANz+u3v5z3PreXX9Hk4+9Uy+ceNX2LC9HTW6j1Con89c82UsyybrMB3ZAj4n1XMXkOjbA7bJ5gNpFh6XRmff2Mu9haNJGvfvBuDJJx7l29+4jmhcx7Jsnlz1KDd99b9ZuPgE2vs16g7sHid1i4B/+AYhA3ndGg5HKg+5t20nTe0RnE4tXeotljDAVrj37rto2L+XL37l6+kd2/kLl/CVr/8Ah8vHnIppKCiTGqRm+F3oZqrzX0GO9/APEEIIcVTI6Q8hJkEkpvPn+57BV/ZuZpTBP55OVUlYeulP2Nz0EoaZSllwOdUDucJHZv2GzWRn55KTkwtAIJjBbb/+C/9z061E0HjqwdtZce4FzK6eSyRuDOnS9mY+jwOX083ChQuJde9iy+4gnAVup0pfJIluvFERYjR6Q0mam5uZf/43KJg2h2ZT49ofvUSmz+axX3+OOTVz+fK37uDX/9yTzj9O6CZ5WYev6KAoCrkZbmrmLuLFe5+nvWcJlmVjGBa6YRGJ6sRjEX7+k++x7IRTOO2Ms9OPtSybqvnn8GLjdipnFWPb4HJO3j6Cz+vAMG2cDpWAT9IrhBBiqsgOshCToLOnnzUbd2DEuvnWfy3m5s8u45ufXILHbsdZeCrf+c1adjf243CoROP6uA++QSp9YeeO7ZRXVg263el0svDUy1Ex0Pv38tkvXEcsYZAVdB12V/ZgbeKlJ5xK4/bnaOmM0t2fOFC2ThnTrrdpWkRiBvvbE+ROX0Tt7Om44jvZ/eqf6O5PsuiCb/KLO+9hT2sSh6ZQNeNggxAb3yjLqmVnuJk7fwmR7r3YNrQeaF+d0E16QgmeffJhwnGb93/8f9iyu4dXNrXzp0d2cP1PX+b3D23H7dIoLQyAYuN0TN4OssupYZoWBdleaeUshBBTSAJkIY4y27a547af4vAWUD49h/xsH1lBNwU5Xk6dY7L+kW8Rjsb5yV83YZo2lpX6in28Onpi7N2zg/KK2UPmsXFnN/PnFPLSmu1U18xFN21yM0dXZzc7w82CJSfT3ZBKCTlYzcKpKXT3x4eMT+omoUiSjp4Ybd0xevoTxJNGqnayYtMb92BbOisvqeEHX/8ohe5merbejSdzOvf8p5VNO7upmp45oNKFgtc9umDV73VSUjqDgDt1MK+pIwJK6qBeJGbw4urtnPyB3/DPV01+ds9mfvuvbby6uZ3ZMzP52MXV3PLZZQS8DlwObVIDVbdTI8PvIifzyLvzCSGEGD9JsRBiHEzTwrTsUeWn7tvfyO9/+yuWX/k76qtnDLpv/sLFdO3/LOWZHaxvyaWlM0qG30k8aR6yBNpAfeEkLoeK26Vh2TbbdzXS29NFReXgAHl/a5i+cJJ5VblomnZgl9rGP8pd2aDPSdXsOpx2GMWMsmV3N6csKMLrdtDTn8QqtlHVVB3fvc0hOnoOBM2KTbgvjt7Qi4ICipJqNOIqwGF04dBUHJqHu/78AJZl8fLmDv7w0A4ATl1YDHCgQYg66nxgh6YS9LtYOL+GLjNJQ2uIuRU5dPclsCyLhk6TvCyTT723noDXic/rIDfTMyhNJJ44fOrJRFNVhfLSjFH/nQghhDg6JEAWbxnGga/uQ9EkPf0Jgj4ns0oyjspzdfbG6QslR9U04oYbbsAVKAJFYVqBf9B9ZeVV+ANBmvesA89ZNLaHqSvPIZ4wRlXiKxRJ8vqeHlQllXvrdTvYsycVXJZXDE6x2LCjG0WBuRUHc3otAj7XqHOHvR4Hqqay7IRT6Gxaw+u+IKaZaqJhmhbRuEHA56SpPUJbd4zsoCvdOdCKO9IHAS3LJhSK4g5OI9vZlL6+oihomsZJ84oIRXQefbGBeVWpucYTJrmjyD8eKDfDzZLlp/KP5xrZvsfNRaeXEY3rNOzfjTNjJhme1IeFkRimPSVNOiQ4FkKIqScpFuItQTcsNu3qZtveHtq6oihAe0+MpH7kNYWH09WXoLMvTjx56FbLr732Gn/+0x848/wPATAtf3CArGkac+sXsHntszgdKo1tkVG3nLZtm4a2MF63RlbQTYbfCdi0Ne0BoLxyzqDxG3Z2UT4tg4AvFYDFkyZ5o0yvANBUhQy/iyXLTqFh67PEEya7m0NAauezL5ygpTNKY1uErAHB8ZupqsJrG/egqBqziodvhHHuidP5/udPID87VcnBMC2yDtFBbzhBX2quke59tHbFcTpVwlGD1a++QDCvktry/EM+3jDtSWsSIoQQ4tgiAbI47tm2zf7WEIZhkxV0E/S5cDk1FBS6+8deguxwdMMiHEvidKp09w7NvR3oq1/9Krl5+cyZfxoup0pe9tCAdN78RWx7fSPFed4DJcnUdEmyQwlFdfojerqRhaKkSpLt3b0Tt9tDUfG09Nju/gSNbZHBO6a2TdA/tt3KnAw3C5aeQnfTehRsNu/qBlJd9dq6YuxrCaUO/Y0QHB+0ZVcHlmVSV1U04piDnfxSqSAK/jHWI/a4NXJzcgi4dQzcxOIGPq/Ga+t3omoOFs+dcdhrjKUyhxBCiLcO2R4Rx72u3jgdPXGyg4NTEnweB62dUQqyvYet0jAW0bgONgS8Dlq6YxTm+Yc9yKXrOs888wzv+8DVdIdMSvL8wwaO8xYsRtd1/I44+9sVNFUhqZvp0m/DsW2bhtYwvmEOre3auY2K2mV86ccvkxlwUTk9M91u+mDKgm5YuF3amLvEBX0uZswsJzc7EyXRysadft59RhlOh0okrpMxijrFAI2dScKdjVSUX3DYsQndIhhwjrgWI1EUhdxMN+UzCmgHdu7roH52EU0dSYoLLCpKMw/zeHBOYok3IYQQxw757S+Oa7GEwe7mfjL8ziFf6TsdKgndHFW6wlj0hpI4NBVNUzF0i3B0+E5yW7ZsIZFIUDF7Hs0dkSH5xwfNm78IgHh/E5G4QW8oiWIrh2w53R9JEorqw7Zd3r1rB9Nq34lp2hTn+diwvYuXN7VTlOul8EDziVjCGFVN4TfzuDWcTo0TTjyVhq1P0dwRpevALnpWwD2qIFY3LPoTHsId28nLLzjs+ETSJDdjfFUdMoMuli6qA+Cl1ZvZumUT7uxygh7jsPnFNjauSSzxJoQQ4tghAbI4blmWze6mfpyaOmJg5nFqtHVFJ+w5bdumqy+eLjfmcWu0dsaGHfvyK68CUD67nkjMYFrB8Pm2RcXTKCgspmXvegAa2yOpltMjBMiplJLwsBUW4vEYzS2t2IE5LKrO41OX1XHrF07gxo8v4por6t84NGfZZB6me95wFEUhJ8PNwqWnsH/LUwBs3Nk9pmvsbQmBouKyukbMUx7Itu1xN81wuzSWLV2CkQizfXcbzz//DJkF1dRWHC7/2MLt1Cb0mwchhBDHDwmQxXErmjAIR/VDnvr3uLV0/d2JEE+aGIadzo/1uDR6Q0Ovn0iarHrqRfz+AL6MVJ7tmw/oDTRv/iJeX/cUAI3tYZyaOmxtYUiVdYvGDDzDlIHbu2cXBRWnYuHg9MWpEmmqolCS7yc7440qEpqmjruEWXaGm4VLTyLW34JHS4w5QN7Z0AdAXuDwtZ5N08LhUEdd//jNXA4Nt9uDavbSHbZ5Ze02NKeb+dUlh3ycblj4PVJNQggh3q4kQBbHrXjCOOwOpKIoqJqSTgM4UuE3pWscvP7Bw3qGaRGO6mzd28OWTeupmzuf5gM7zCX5fiJxnd5wkr4B/1mWzaIly9mzYzOZfo2m9gg+j4Ou3gR94cHpG4ZpsbspNOKBtV07d1Ba9y5yM1TKpw1f4i6WMMjJcI97d9TncVJcUkphUTFG30627+8lnhj9B5CdDf1EexuZXpr64GDZNrphEU+axN50nVjCJCfDPaqd5uGoqoLP46Aw243DV0BDR2o9K0oPXf7PMC28HkmvEEKItysJkMVxKxTRcWqHD5wCXietXTFMa/ztmw/q7k/gcQ3+sQl4HDR2RFi/vZPVr3fw+u4edN1gx7bN1NUvoLkjVfYs4HNiGDbl0zKYPTOT2TOzmJbvoz+S5IyzL0RRFMxYO03tERQlFdjtbe4fNO/GtjCmaY3YMGPzjmaCeeWcuaR0xKBSN6wj6tTmdKgEvE7mL1zG7o2PY5g2W/f2DhlnWTZtXVHWbO1kW0OEaNzAsmx2NfTR07yJ6TNmEY7qhKM6pmXjdqk4HOqgDwW6aaV3vscr4HNSXTUdh8tHfvmpBNwmGf7hUzYs2yYWN4gnLbyygyyEEG9bR62KRUNDAx/+8IdpbW1FVVVWrlzJ5z//ebq7u3nf+97H3r17mTVrFvfccw/Z2dkA3Hzzzdx5551omsZPfvITzj333KM1PfEW0B9JjqrbnKYqmKZNOKqPqvnGSEzToj+cTHW6SxjpA3KapuJzO1BVJV0VYuvrm0gk4tTVz2dDe4SSfP+BcmUM2r3NDLjIzvCwL+BiyfJT2bftFfJm55LUU530esMJ2ruiFOf7CUWStHbFBlXriCdNTNNKp5ns7/FhOmOcvGAaw3mjZNqRBX85mR7q5i3m8ce+yezTv8iGnd0smJMHQFN7hD8/upOGthC68UZwrzzaRH6Ol4Ru0duymRkzT8cwbarLstIBq2labN/XS380SdDrRFFSO9ZHwu91UDtnFs9u2kogZya1FanfN4ZpEUsYWBYc+KtBUSA76GZGcfCI/q0IIYQ4vh21ANnhcPCDH/yARYsWEQqFWLx4MStWrOB3v/sdZ511Ftdffz233HILt9xyC9/97nfZsmULd999N5s3b6a5uZmzzz6b7du3o2nyNacYyjAtEro5qEyZaVrsbw2zo6GPfS1h3nnSdEoLAwA4HQrdffEjCnqicQPLtunoifOtO1bzsXdXs/BAUPjmHd3NG1MH7qpr5/Pv+9qpLc9GNyx8HseQ1Aavx8GcmVlcceUHuOXHvyO36p00d0SZVRIkw+eioS1MRsDF7qYQPo9j0EG77/9+HU0dUfKzPMwoDmB4ZqL0bcHjPmfY1xBPmmQGXWMumfZmQZ+T+gVLsS2TXF+cTTu7sWybnr4EP7l7I5FImKat/6G7ZRtKspukqfCFr/2U1h6LaLif7sZ1lE6fBYo96O9Q01QqZ2SxdW8PvaEkQb/ziGsRe1wOivLeyP+urUhVzghHdQpzffg8Gpqm4dAU/B5HOr9cCCHE29dReycoLi5m0aJU+apgMEhNTQ1NTU088MADXHXVVQBcddVV3H///QA88MADXHHFFbjdbsrKyqisrOSVV145WtMTx7l4woQBGRMPPLGJa259hlt/v577ntzLmq0d3P+fnen7vW4HXX2JI0qz6Akl0VSFjTu7MS2bJ19rHnHspo1r8QeCeDNKMEybafl+dMNKd7F7M0VRuPTSSzCibQA0dUSAVA6t06GyY38fCX3wwbxXt3TQ1BHl5PlFlBb62d0UwrJsSjNCI84roZvkHUF6xUFet4Oamnrcbg/x7q2EojpbdvXwk79uIhqL88I9X2RmoJUf33wdd/3uTrob19Gy+QGuuaKemY7XMBL9FBaX4nU7hgTATofK7BlZuJwquWPo9DcSl1PF43Sk00qqpr+Rf1yc5yM/20dOhpsMv0uCYyGEEMAkNQrZu3cva9euZfny5bS1tVFcnDpdX1xcTHt7OwBNTU2ccMIJ6ceUlpbS1NQ05Fq33347t99+OwCtra00N48cpLyddXR0TPUUjqqeUIK+3ghWwkljR5xHXumkt3kzjVseSX19P+9isN/Dnr2NZAZSQWkoarBrT5TAGNILDq5jLGGwq6GfgM/J+m2tAOzY38e2nQ3kZw3dlV6/9jWqZs9hx54WAALOOJ0d7XhUP8328AGskTBYungeCT3Otl0t1Ex7Y6c5Ejfwuh10HzhraFo2/3x6L0U5bs5bGkRVFFqaY1xy8eVc/9Vv0N3ZNuxzhKIG4YBOInrkgaBGhNlzatn62oMULJ/HL/++BUWB0Pa7yQ6o3PiN76R3u5edcDJ//v2vufx9H2Tn9i3kFxTS09NDTqaH5ubhux3m+Cz0WJLm5t4jmqdt24T6einKdoJlgd5He1svpmXT2XF0WpEfLW/1n+vJIus4MWQdJ4as48SY6HU86gFyOBzm0ksv5cc//jEZGSOfHD+YnznQcIeMVq5cycqVKwFYsmQJJSWHLtf0dvZWXpt4Ux/5BFFVhb/du5pktIfKjH3c9fDfAPjWt75NF/Dy1j6uOC/VKMId03F63JSUHLqCwZsVFhaxeXcPRUU+VFVhb+tOltTms3ZrJxv36VxWOX3QeMMw2LljG1d+8Gr64qnOcrMrSwlHdaZPzxkxQNcNi0ve+2HueGAnO/cr5OQtTN+XM2BcJBLmLw+8SHe/h8ZXf8UZP3gcANuywLaon7+YnLzCIddP6iaBTJg5M3fIfePhDSSYv/gk/vqn21n+ngB7msN86JyZfPz2v/ORj32a3Pw32kh/8MMf53Of+gjPP/8M7e1tzJxZTiAzj/JZWeOqxzxWId3H5efmoAA5OV7CUZ28LA8lxcGj/twT7a38cz2ZZB0nhqzjxJB1nBgTuY5H9ftEXde59NJL+cAHPsAll1wCQGFhIS0tqV21lpYWCgpS+YClpaU0NDSkH9vY2Cj/YMSI+sM6bqfKvY/voqM3zuZVP+Bd73oXbo8Ht8fDypUfo7thDc+tbcE0U/V2R5NmYZhWevxBLZ1R4snUobydDf3ohoUzvpu68kxe2tiGbgwev3PH1vQBvab2MMW5XhyaiqKAe4TqE5BKLVi87CTseCfdYXvYD43bt23h1BPm8tymPsKduyjNtfnI1Z/iox/7NFd/4rNce91NLFy8HEjlKCd1M32dWNIkN8s7ugUeBb/XkWqTnUyypCzBFz8wj/a9L2IYBuecd+GgsYuXLGd2dS2//80v2b9vL9NnlqGgjLnV9XgFfE58Ho2CA50EddMmQw7hCSGEGMFRC5Bt2+ZjH/sYNTU1fPGLX0zfftFFF3HXXXcBcNddd3HxxRenb7/77rtJJBLs2bOHHTt2sGzZsqM1PXEc0w0L3TBZt72LFza04YxsglgzS5efnB4zc1Y5hb5uTNy8tD71wUtVFSzLHlLLeKDGtjBrt3XS0hlFNyyiMZ3G9ki6ysKW3T2ois3NN3yU/RsfJBIzWLutc9A1Dh7QM32z2byrh6oZmZgHmnMc7sBZht9NVVkhiuZh2459Q+6//x93kzvrVLzBQr608nxuu+NPfOn6b3DtdTdx7XU3sfJTX0gfbO2PJrFsm76wTm8ogWFYE1qZweXUWH4gLWr3669SOT2Tfz/yL4qKS6g/0D77IEVRuOrqT7Ft62Y62luZVjoDl0sdsVzdRPN5nJjmwA8c9qQF50IIIY4/Ry1Afv755/nDH/7Af/7zHxYsWMCCBQt4+OGHuf7663n88cepqqri8ccf5/rrrwegrq6Oyy+/nNraWs477zx+/vOfSwWLtzHbTu1+RmI6kdjggDaeMDAtm3se38WMIj8v/vP7vGPF+TgcgwOeT1x1CbH+Nu5ftTl928FqFiPpDSXxuDQa28Ks29bJvtYwfo8D9UC6z+bd3YQ7toFlcP8ff0CmX+W5da2DrrF50zrKFrybf68OUVOezSXvKEfXzVHlPgf9Lk47OfXB8IGHnxxy/39WPU7F0iupKM1g3uyR2yVbto2CQk1ZDotr8qgtz2HOzKxxd6QbyZyKGZROn8Xa1a8QjUZ49ulVrDj3AlR16K+WCy+6jOycVHpHUckMsiZxB9ftVIHU36F5oI30aEoECiGEeHs6alsop5xyyrBfEQOsWrVq2NtvuOEGbrjhhqM1JTFBLCv19f/ROvHf2RNjd3PqIJtip/6nriI33Ro5ljDoDSfpj+jMKYzS39/DOeddMOQ68+YtxHHnw4QzTmNfUw8zp2WnDrr1J5hRbKO9qdxaUjdJ6hY+jwuXU8OybKJhNR1IdfcnaO2K0bTjBf7vuz/lu9+5kfbtq+ibdiatXVGKcn0A7Gx3Ubb8auorc/jEe2pwOlRiCYP87MMHyD6Pxvy5ldy76gm2hXwYppUuybZ71w7IXIjiDHLhaTMP2V0uEtPJz/akd6wDPhWY+MYXGX4Xc+cvYfXLz/LMU0+QSMRZce6Fw451ezxc8YGPcttPv0/RtJmTknucfm6Xhn2g7Ek8aZIdnLznFkIIcfyRmkZiTBJJk+37e1m3o4tQJHn4B4yRbds0dUTwexxkBVzpmr2NreH0B67+iE5bRxSAHRuewR8IctLJZwx7vfdffDKWqfOH+54HUmkWhmkN2ZWGVFvjgbXjVFXBPSAlYtPOVCpFtjvMey67ki9cewOvrPotCjZ/fHgHP717E1/5fy/hn3keXquVlZfUpANUy0rVOz4cl1PD6VCZXxrHHSzhzw+8nL7vwUf/w8yFl1E3y8+cmVmHvI5h2ORnT1y+8Ug8bo2Fi5fR0dHGb+/4OTm5eSxZduKI4z/+yWv45v/9kNq6BZPaytmhqbidGqZpoZsWGRIgCyGEOAQJkMWodffF2bizi2jMwO1Q2bK7h9au6IjfFIxHOKoTT5qDcnX9XifdoTj9kVRQ2x9J0tQRwaEpPP3Y3Zxx5grcnuHr5Z555ukkurbQ0O0iqadKejk1lZ7+oaXFojF9SBOPgVY9t4l4uJNPfuKjKIrC5VdeRcWsUnr2v8je5hB9kQRZ7hBbn/kFp9Xab2rGYR/ygN5BqTE2H7j0bLobVvPS1jjd/Qksy2ZjcwZYSa66eO4hrxFPmgT9ziPuljcaiqJw+qmnALBu7aucteL8Q6ZGBQJB3nvlR3C6HKNaj4kU8DpJGtaBw4GSXiGEEGJkckpFjEpDW5im9jBBnysdvGqayt6mfiIxnbKSjEMGl6PV0RPHNcxBNr/Hyb6WEHNmZmEYNg1tEbJ8Nl2dbaw4b/iv9CEVwC2pyWNzl5enXtrMOafOw+tx0NkXZ3phYNCceyPJEYO2eCJJSy/Ykb2cteILAGiaxte+cQsffN8F1M1dyEv7dhEK9eP1+li69Ltvmgi4RpHzqqoKfo8T23ZQ4tlL1JzLXx/bwfR8J45AKdOcOwj6Dp27G0sYVE3PPOxzTZRlSxfg8/mJRiOsOPeNVBfTtEjqFknDIhTTcUV13C4N3bDI9LsOmSJyNPh9Trr742gOdVDDFSGEEOLNZAdZHJZp2bR1xcgKugft7GqqQnaGm46eOOFhUhbGSjcsuvriw6YiuF0asYRBc0cEy7bZ3xom1rsXt9vDaWecfcjrvuf8U9ATYZ5+eVd63qZhE0sY6TGWZROO6Licw/9I3PHbP6M5fZx5Uh2KkqqGYZgWS5efzKWXf5D29hbOeedF/OyXf+C5V7cyrXTGoNflcTmG5DyPJOBzohsWl777Ivas/isbdvbw8IttdDWs4T3nLh4yPho30uXcTCu1c505iSkEGQEPc+ctJhAMcuJJp2HbNj39CRK6hd/nZEZRgBmFQfJzvFi2TTxpkB2c/BJrPo9GLGFOSXAuhBDi+CI7yOKwojEdy7bSlRwGUhQFl0Oluy+eLoU2Xj39CXbv2sY1K9/HHb/9K9W19YPuD/qcdPTE6O6PE0+a7FuzipNPPRO/PwCkgtxE0iShW4CNjUJ20MW00lKMvn/QqVWnD70pKvSHk+k0hHjSTFV+GOY1rnntZZ7b2E92ic5lF54JQH9Ux7ZtsoNuvnPrTw/5unTDIiMw+nQHv9dBW7fNiSefTuK6L2AnLwBHkJ7t/6B27jWDxkbjBqqqoCgKfZEkpmkzoygw6mB8Imiqwte/dTNNTa243G56QwkKcrzMKgmm19NMOCkpDDC9MIBhDv9v6Wg7mN+dNQXBuRBCiOOL7CCLw+qLJA8ZcPk8h2/AcTi2bdPaFeW1F5+kva2F237+wyFjHAfqCD//4hoAEn0NfOFLqaonpmXTF07i9zkpLw1SV5GDw5E6kAcwZ7oX1eHl5XV7U3N2O+jofaPcWzxhMFzM1t3dxTe/91tyShfy7tNnDsrrdTq0dF7zoSQNk6Bv9AGyx+0AbDRN48KLL+HFe69lzQNf4bSTlw8J4ONJk/JpGdRV5LC4poD5s/PS1TQm04nLF7Ng6cn0hpNkZ7qZWRwccZfWoakTko4zVm6nRsDnxO85+rnZQgghjm8SIIvD6uyNH7KpwsHKEIdqwHE4kbhBLG6wYd1rAPz7kX+yb+/uIeMeuv/P/O3+R7DMJHf97rfMqU61ke4LJ5k1LUjl9Ezysrz4vU5K8vxEYqk0igvPOQEjEWHVC1sB0qXX4snU/f3hJM43la0zDIObvvltCusuZXqeg3NOLgdSubUOTaG0wEd0QJrGiGwFj2v0X9a4nRoHw8f3XHYl8XAXve27eMfZ7xw0LhLTyQm6CRwIvjVVwedxHLXye4cS8DqwTJuA10H5BOWjTzRVVSgtDOCRA3pCCCEOQwJkcUixhEEyaaJgY5pm+r83O5hmMV6dPTEcmsLa1a9w8qlnojkc3Hn74NSFP//hTm78ny9QUr6YsmlZlE5P5fmGoklyMtwUvKmsWW6mG9tO1Wyuq5tLpGMTzX3OdCtpVVHSQX1fJMn+1jD/87OXue/JPfSGEnzvlm9g5Z6O2+3iv963KJ0WEEuY5GS4yc7woKBgHa6Kh8KYmlI4HSqapmJaNhWVc6ifv4hAMDioU6Bt2yR0i2mF/lFf92hyOTVmlWRQOT1zSgL00crJcEv+sRBCiMM6dt/JxDEhHNX5812/orYiL/3f/OpiHrjvr4PGed3jT7NI6ibt3TF6u1vo6Gjj7HPexSWXXsl9f/sLzc0tWJbNpo3r+M63v8rpZ56DJ7OU8tKs9GNBGZTvepDLqZGb5SEaN1AUhbJCFUXzsH5bqvOd26nS2RtHNyySusnGnd30h5M8/nIj1//kRda3TSOruI73v7OanIw3Dr3ppkV2RurAYl6Wh2hs5F1kw7TQFA7bYvrNgl5nOn3jO7f+lJ/96o+4XG/kzkbjBrmZ7kkp5TZaRXm+SWsdLYQQQhxNEiCLQ+rqi/Ov+/5E1exqrvniV7nmi19ldnUd3/nWV+nr602PU9VUZYfxpFl09sRQVYV1a17B4fLTpc7FMesKlr3vDr59107+31/W8/lPf4Tc3Dz++2s/IqlbzCwOYts24ahB5fSMEQOzgmwvSSO1Y/zOdyzBSEZ5/LnXgdSubn8kSSiqY9sKe5pC5AZMtjxyPa3bnyCnpJbamX5OqC8YdE1FAd+BPNb8bC+GOfyHAt2wCEV0yqZljHnXMuB3oR+Y9+w5tZx40mnp+2zbJmlYTCsIjOmaQgghhBgdCZDFiAzTYv2GzezetZ0rP3g1n7nmy7zzkk+y4IL/I1h6Cj/50c2DxjsdypjTLAzTorkzht/rZO3qVyhb+B627E+SleHHbbXStfcFtu8PkXQU8aOf/YbeSCoQnlkcSLUMznQfsmVxwOfE43KQ1E2WLz+Rvua17OuwMU0LRVGw7VSOtWlZ7G/t57Vn7yfohe/d8AF++MWTueLskkHBbVI3CXid6R1hv9eB2zX0sJ5upHKyZ8/MJCdz+CYmh+LzOEYMvCMxg7wsT7r1thBCCCEmlgTIYkSRmMFTTzwEwJlnn89Dz+3jB39cT3fIpuqkj7OuMZNNmzenx48nzaK7L4FlW2iqwro1rzGt9lzmzMzkmivr+dT7lrDh8e8R6W1kyTuvZf6CpextCeF2aRTkeEnqFlmBQ5fsUhSF4rzUYTqn00lxZhJbdfP63h4glTvdF0rQ0RPHshWIt/G3+1dRNbsGj3to7eJY0iQ7wzPs9YFUnd+EQTiqM2dW1qCxY5Hhd5IVdA1piW1aNoZlMa3g2Mg9FkIIId6KJEAWI+oNJXhq1cMsWn4mf17VyYPP7mdJbT7f+exyzl1eQH7Zyfz0nu20dkWBsadZWJZNc0cEv8dJJBKmrV9FdWVy8oIiAOrnLeSid19GvrqbuOnhuXWt7G8JM6MogHpg93e4piJvlp3hTh2ms2zOPqUeU0/wxHOpwN7rdhBNGOzc3wnA8oWzR2xbDWBbqeD1zdfXVJXeUIJwVMfp0qguyyLrCJp1KIrCzKIgScPCGvCBoz+cZEZRcExVMYQQQggxNhIgi2HZts36zdvYumUDFcs/zP7WMB+5cA4fvagan8fBu98xh/r8Rgzbya2/fTUdxDkdCh09sVE9R38kSVK3cDpUNq5fS9HsFbgcNgtm56XH3PrDX/L973yV2TMyefDZfTS2h5lZ9Ebu7WhaBh88TBdLGJy94lxC7ZvZtj+MbduoqkJxro/VG3YTC7Vx4YXnj3gdy7LRVIaUvHM6VGrKspk/O4/FNfnUzMo+ZNrHaHk9DqYV+OmPJgGIxQ0CPueQah1CCCGEmFgSIIthtXXHWPXYQ4BCTMln/uxcls8dfFjtk1e/j9DufxHTVXbs7wVSubPdffHDNtCwbZum9ki6Ju2rq9eQN2sZy+ryhlR8UBSFS88qJxIzMEybGcWBVC1ihzLqqgk5mR50w8br9TG71AuOIKs37kzf39JtkOxvYMHCpSNeI540ycpwD1vj1+dJ5SJPdAmx4lwfLodGPGkST5rMKgkekzWGhRBCiLcSCZDFEN19cfY2h3juyUeYt+w8onGL+oqcIeMcDgcXnXMCph7nqVdSTT1SAaJCT3/ikM/R0RMjFNXTO8Cb9sRQNSfvWDZr2PEzigIsP1BNYlZxkKRujam1dcDnTKeAfOjyc7Fti7/961kAGpo6UZxBZhX7UdWRfyQSujXunOLx0jSVsmlB+sNJphX6j6mybkIIIcRblQTIYpD+SJId+/tIRLpYu+YVapZdiALUlmcPO/6008+gc/+rbN7Tnz6c5/c6aOmKYo/QQKM3lGBPU4jMAwfsTNMk6S7HYXRSnDdym+TLV1Tw6ctqyc/2kjStIbnAh6KpCrmZbmIJg8rymah6J009KuFwiIf+/RwAZ568YMTHxxMGHpdG5hiec6JkBtxUl2VRPAUtpIUQQoi3IwmQRVo0brBtby9+r4Mnn3gklaMbmEXZtGC6nfGbzZhZhtm3Dd1ysGN/H5DKyU0mzWEP60XjBjv29xHwOdMVIp595XU8GcXMLj70/LxuB/VVuUAqH/hQ7a+HczDNAmBpXQmB3Ar+es+9rN2yD8vUOeOUxcM+zrJsYkmTiukZU9YlLi/Le0x3qBNCCCHeSuQd9xgQjUaJRCJEIhFisdEdcDsaUg07Uh3oHn/sQSqrF9HWYzB3mPSKgeZV5mHqcV7b0pa+zelQ6egZXBM5qZts29uL26mm84wjkTD3PrIOPR5ixSm1o56rqoBnjAFywOtAUVKl2M45fR4ADz7+KqGkB68WwenQsCx7SOvo/kiS6QV+ApLeIIQQQrwtSIA8xb7xjW/g9/sJBALp/+64444pm4+qKIT6+3jlpedYfPrlAMytPHSAfMppp9O57xVWb2lPp1l4PQ46+2LpbnCRmM7re3qwsdOB7cYNa7n8vZdieqZT5O+lunrOqOZomhZOhzbm9s2appKT6SYWNyjJ8+F1GriyawjkVVBdlg9AXzhJfyRJXySJadkkdBOvx0FhntQdFkIIId4uJECeQi0tLdx6662ceeaZ3Hrrrdx6660sW7aML3/5y7S3t0/ZvJ5/7ikMw8BfUEdW0EXpYZpSnHDSaXTseZ64Dtv39QKpQBugpz9Oe3eUTbu6UYCA14llWdx+24+54pJzCEw7GU1V+fKnLxtyXcuySermkIoYCd0aMeXjcPKyPOhGqovesvpScqYvRHO4WTq/IjVvFerKcyjO8xGO6iQNi4rSzCENQ4QQQgjx1iXdBqbQd77zHZLJJLfffjuVlZUAXHDBBcybN4+vfe1r3H777VMyr6f/82+ysnNp7VVZUptz2NJlmZlZFGVY2GaCNVs7qSlLHejzuR3saQ6BDRkBF5qq0NbazFe++CleeuEZzrngvSgz38Himvz0gT2AUDSJaYKmKXhcqRJntg3uAxUvkoZJZmB8O7oBrxNFUbBsmwVz8nl6TSsAZdMy0A0Ll1PD73Xi9zopzPGxvyEuLZ2FEEKItxnZQZ4i+/bt41e/+hVXX311OjgGqKmp4XOf+xy//vWvWbNmzYQ+ZzQa5cc//jGdnZ0jjrEsi2eeeoIT3vE+4klzSP6xZdn0hBJ09ycG7eyedMoptO95mTVbO9JpFi6nhs/tONBpTuHxRx/kovNOYcO61fzfrT/l/Pd/Dd2wOWtZafo6tm1jmlBflcPimnzqKnKonJ5BJG68MQl7aLOO0RqYZlE1PQOvWyMr6CInw01SNwcF6k6HOu7nEUIIIcTxSwLkKfKtb30LRVG48cYbh9z39a9/nby8PK655poRS6WNxy9/+Uv++7//mxNPPJHt27cPO2brlg10drZTUnUKDk1hzqys9H3xpElfOMmMwgA1ZVnEkxaRWKpSxSmnnknbrmeJxk1e39OTfszBXd+nn/w3n/2vD1E6Yxb3PfQ07770/Ty9uoWaWVmDUjjiCZPMoGtQYJrhd5EVdKWfC4V0g5HxyMvykDQsNE3l/JNncNayaQDopkXGBHTAE0IIIcTxTQLkKbB9+3buuusuPvWpTzF9+vQh92dlZfGd73yH559/nrvvvntCntOyLH7xi19QU1NDb28vJ554Is8888yQcc89/QQOp5c+I5uq6ZnpRh6hiI5t29RV5lCc7ycz4GZuZTYul0ZvOMG8BUuIdW5FsRM8v751yHUff+whgsEM/vK3R5lVVsFrWzroCyc5e3npoHHxpElR7uBWyoqiML0wQNKw0A0Lt1PDcQQlz/xeJwoKtm1z9vJSzj64g22DdxStq4UQQgjx1iYB8hS46aabcLvd/M///M+IYz760Y+yaNEirr/+egzDGHHcaD322GPs2rWLm266iZdeeon8/HzOPvts7rnnnkHjnnv2P5xwyf/RF9bTwattp0qf1ZbnDCp15nE5qJ6VTYbfhWVrLF22nJ59L7BhRzf9keSg6774/NMsO+EUXC4X8aTJYy82UJzno6YsKz0m1T5aJeAb2iEvlRPspas/TvAIm3U4NJXMgJNE8o0UEcu2URQlveMthBBCiLcvCZAnkGVZhx2zefNm/vrXv3LNNddQWFg44jhN07jxxhvZv38/jzzyyBHP7Wc/+xlFRUW85z3voaKighdffJGlS5fy0Y9+lJ07dwLQ3tGOlXMqrqxK3v/OqnT3vHgylZs7XFk1TVUozPER1y1OOuVMtr58D5Zl8+KGN2oiNzTso7FhHyeefDqWZfPbf26lrTvGZWeVDzoAGI4bFOd6R6wYUZLvx+PUxtRieiS5WR7iA3Kok7pF0J9qRy2EEEKItzcJkCfIyy+/jNfr5fzzz+fRRx8dMVj+9re/jd/v50tf+tJhr/mud72LoqKiI66LvGvXLh555BE++clP4nKlgsvs7Gz++te/4nQ6+chHPoJpmtz+15cpmn0my+e4OHl+UfrxCd0kN3Pk3Nyg34kCnHr6WUR7mwg6wzy/vjWdP/3SC6lUjhNPPo37ntzDhh3dvPfs8iHtqy3LJjvTM+LzuJwaVTMyCQ6zwzxWQZ+LgendqQN6kn8shBBCCAmQJ8zNN9+Mx+NhzZo1vPOd76Smpob77rtv0JgtW7Zwzz338LnPfY7c3NzDXtPpdHL11Vfz0EMP0djYOO653XbbbWiaxsqVKwfdXlpayk9+8hOef/55rv3mb9nVFaRz13/40MVLBo2zbYZNezjIoalkB10UTytj3vzF7N/4MB09cbYfaD390gvPkJ9fSEs4kydeaeKMxcWcuWTaoGvEEwYZftdhq0ZkZ3gmJA3C7dLweRzpShy2DX6vVKwQQgghhATIE2LHjh3885//5JprrmH//v388Y9/xOPxcPnll7Nq1ar0uIO7x1/84hdHfe2Pf/zjWJbFb37zm3HNLRqNcuedd3LJJZdQUlIy5P4PfehDXHTRRfzmZzfRsuVBZma0o2lvBKC6YeFxOQ4blOZle4nrFu++9H2sf+4e3E6F59amdpFffuFZFr/jw9z92E7qyrO57OyKIY+PJU2Kcn3jeo3jlZflJZY8GCDb6QOJQgghhHh7kwB5AvzoRz/C6XTymc98BpfLxQc+8AGeffZZqqurufTSS9m6dStbtmzhr3/9K5/97GfJy8sb9bXLyspYsWIFv/71rzFN8/APeJPbb7+d3t5ePvOZzwx7v6Io/OpXv8KpxHn92ds57fSzBt0fSxjkZx0+9eBgmsU73/UeNNXGldzLuu2drN2whdyay0hmnUp5aQYfe3f1kBxj40Dr6IzAkadOjEWG34ll2Rimhcul4XJKgCyEEEIICZCPWGdnJ7/73e/40Ic+RFHRG3m7GRkZ/Otf/8LtdnPBBRfwla98BZ/Px7XXXjvm51i5ciUNDQ089thjY3pcQ0MDN954I+eeey6nnnrqiOOKior4zW9+w9z6BSw/6YxB91mWParawAfTLLz+LE4/8xxWr/othmnzm0c6KKk5l5PqMvjC++cNm0IRiRmU5PsmvZ2zz+PA4VCJxg2yJuDgnxBCCCHeGiRAPkK33XYbsVhs2LSJWbNmcf/999PY2MhDDz3E5z73uTHtHh900UUXUVBQMKbDerZt8+lPfxrLsvjlL3952HbRF198MQ899gyBQDB9m2XZaJo66lbL+TleEobFuy+5gsZda8gPWphGksZXfsGHLpo/bABsWTaKArmHOJx3tCiKQl6mh1BUn/TdayGEEEIcuyRAPgLxeJyf/exnnH/++dTW1g475sQTT+SPf/wjJ5988rh2jwFcLhcf/ehH+de//kVzc/OwY5LJwXWHH3zwQR588EG+/e1vM2vWrHE9bzxpkhV0jbr0WcDnBBtOPeNssrKy6d36R9b843PMn1Mw4mPCMZ2CHN+wJeQmQ3aGG6/bgUdaSgshhBDiAAmQx8kwDK655hra29sPG/hedtllPPfcc+PaPT7oE5/4BJZl8bOf/WzIfffccw8+n49LLrmEp556ip6eHm688UYWL17MNddcM+7nTOoWORmj39l1aCo5mW4sHJx/4SU89uDf6O1u54QTh0/vsG0b07TJz5783eOD/B4H2UGXHNATQgghRJoEyOPQ39/PhRdeyB133MH111/PmWeeedSfs6KigksvvZRf/OIX9Pf3p283TZOvf/3rFBUV8cwzz3DmmWdSXl5Od3c3d9xxBw7H+HdGFcUec+mzvCwPSd3k3Zdckb7thJNOG3ZsNG6Qk+k+bGm3o0nTVGbPzJIGIUIIIYRIkwB5jBoaGjj11FN5/PHHueOOO7j55psPm987Ua677jr6+vr41a9+lb7tH//4B9u2beOHP/whDQ0N3HnnncyZM4cvfelLLFy4cNzPFY7qBP2uMVd2CPpdaJpK3bxFlJVXMXtODXn5w6dYJHWT4jz/uOc4USbr708IIYQQxwdJvByDeDzOKaecQm9vL4888ggrVqyY1OdfsmQJZ511Fj/60Y+45pprcLlc/N///R9z5szh0ksvRdM0rr76aq6++uoRc5VHI5YwUFWF8mkZY36spioU5npp7Yzy89v/CNjDjgtHdTL8LmnOIYQQQohjjkQnY+DxePjud7/L3LlzmTt37pTM4brrruOcc87hj3/8I4WFhaxfv57f/e53g5p7HImkbqV2gMuzx10XODfTQ3N7hIrK2cPeH0+aoChUTM+U3VshhBBCHHMkQB6jK6644vCDjqKzzz6bhQsXcuutt5Kdnc2sWbN4//vfP2HXt2ybullZeEdZ2m04XreDgN9FPGEMqQ6hGxaJpEFteY405hBCCCHEMemo5SBfffXVFBQUDNpp7e7uZsWKFVRVVbFixQp6enrS9918881UVlYyZ86cMTfEeDtRFIXrrruO7du38/LLL3PdddfhdDon5Np+r5OasuxUubYjVJzrS7dxPsiybEJRncrpmfi9EzNnIYQQQoiJdtQC5I985CM8+uijg2675ZZbOOuss9ixYwdnnXUWt9xyCwBbtmzh7rvvZvPmzTz66KN8+tOfHldb5beLSy+9lIqKCoqLi/nIRz4yYdfNzfKQFTx817zRyPA7cWgqppXKQdYNi95wgpnFQbLHUDpOCCGEEGKyHbUA+bTTTiMnJ2fQbQ888ABXXXUVAFdddRX3339/+vYrrrgCt9tNWVkZlZWVvPLKK0drasc9h8PBww8/zBNPPIHHc2wGm5qmUpDtJRLTicYNonGD2TOyKM7zTfXUhBBCCCEOaVJzkNva2iguLgaguLiY9vZ2AJqamjjhhBPS40pLS2lqaprMqR13Zs8e/gDcsSQ3y0NTRwSPS2XOrKwprXcshBBCCDFax0TEYttDS4GNVN3g9ttv5/bbbwegtbX1iMqZvZV1dHRM9RQAyPbo+L0GPV1xeg4//JhzrKzj8U7WcWLIOk4MWceJIes4MWQdJ8ZEr+OkBsiFhYW0tLRQXFxMS0sLBQWpBhKlpaU0NDSkxzU2NlJSUjLsNVauXMnKlSuBVF3gkcYJZG0miKzjxJB1nBiyjhND1nFiyDpODFnHiTGR6zipnfQuuugi7rrrLgDuuusuLr744vTtd999N4lEgj179rBjxw6WLVs2mVMTQgghhBACOIo7yFdeeSVPPfUUnZ2dlJaW8s1vfpPrr7+eyy+/nDvvvJMZM2Zw7733AlBXV8fll19ObW0tDoeDn//85xPW+EIIIYQQQoixOGoB8l/+8pdhb1+1atWwt99www3ccMMNR2s6QgghhBBCjMqkplgIIYQQQghxrJMAWQghhBBCiAEkQBZCCCGEEGIACZCFEEIIIYQYQAJkIYQQQgghBpAAWQghhBBCiAEkQBZCCCGEEGIACZCFEEIIIYQYQAJkIYQQQgghBpAAWQghhBBCiAEkQBZCCCGEEGIACZCFEEIIIYQYQLFt257qSYxXXl4es2bNmuppHJM6OjrIz8+f6mkc92QdJ4as48SQdZwYso4TQ9ZxYsg6ToyR1nHv3r10dnaO+XrHdYAsRrZkyRJee+21qZ7GcU/WcWLIOk4MWceJIes4MWQdJ4as48SY6HWUFAshhBBCCCEGkABZCCGEEEKIASRAfotauXLlVE/hLUHWcWLIOk4MWceJIes4MWQdJ4as48SY6HWUHGQhhBBCCCEGkB1kIYQQQgghBpAAWQghhBBCiAEkQD5OXH311RQUFDB37tz0bevXr+fEE0+kvr6eCy+8kP7+fiBV88/r9bJgwQIWLFjAf/3Xf6Ufs3r1aurr66msrOSaa67h7ZZhMxHrGI1Gede73kV1dTV1dXVcf/31U/JaptJE/Xs86KKLLhp0rbeLiVrHZDLJypUrmT17NtXV1fz973+f9NcylSZqHf/yl79QX1/PvHnzOO+888ZVO/V4NpZ1BNiwYQMnnngidXV11NfXE4/HAXmfmYh1lPeZifv3eNCY32dscVx4+umn7dWrV9t1dXXp25YsWWI/9dRTtm3b9p133ml/7Wtfs23btvfs2TNo3EBLly61X3jhBduyLPu8886zH3744aM/+WPIRKxjJBKx//Of/9i2bduJRMI+5ZRTZB3t8f17tG3b/vvf/25feeWVhxzzVjVR6/j1r3/dvuGGG2zbtm3TNO2Ojo6jPPNjy0Sso67rdn5+fnrtvvzlL9s33XTT0Z/8MWQs66jrul1fX2+vW7fOtm3b7uzstA3DsG1b3mcmYh3lfWbi/j3a9vjeZyRAPo68+Rd7MBi0Lcuybdu29+/fb9fU1Aw77qDm5mZ7zpw56T//+c9/tleuXHmUZ33sOdJ1fLNrrrnGvv3224/OZI9hE7GOoVDIPvnkk+3Nmze/LQNk256YdSwtLbXD4fDRn+wx7EjXMZlM2nl5efbevXtty7LsT37yk/avfvWryZn8MWS06/jQQw/ZH/jAB4Y8Xt5nUo50Hd9M3mdSxrOO432fkRSL49jcuXP55z//CcC9995LQ0ND+r49e/awcOFCTj/9dJ599lkAmpqaKC0tTY8pLS2lqalpcid9DBrrOg7U29vLv/71L84666xJm++xajzreOONN3Lttdfi8/kmfb7HqrGuY29vL5Bay0WLFvHe976Xtra2SZ/3sWas6+h0Orntttuor6+npKSELVu28LGPfWxK5n4sGWkdt2/fjqIonHvuuSxatIhbb70VkPeZkYx1HQeS95k3jGcdx/s+IwHycew3v/kNP//5z1m8eDGhUAiXywVAcXEx+/fvZ+3atfzwhz/k/e9/P/39/cPmgSmKMtnTPuaMdR0PMgyDK6+8kmuuuYby8vKpmv4xY6zruG7dOnbu3Ml73vOeKZ75sWWs62gYBo2NjZx88smsWbOGE088kS996UtT/Cqm3ljXUdd1brvtNtauXUtzczPz5s3j5ptvnuJXMfVGWkfDMHjuuef405/+xHPPPcd9993HqlWr5H1mBGNdx4PkfWawsa7jkbzPOCZ68mLyVFdX8+9//xtIfXp66KGHAHC73bjdbgAWL15MRUUF27dvp7S0lMbGxvTjGxsbKSkpmfyJH2PGuo5LliwBUkXJq6qq+MIXvjAl8z7WjHUdX331VVavXs2sWbMwDIP29nbOOOMMnnrqqal6CceEsa7j4sWL8fl86TeA9773vdx5551TM/ljyFjX8WBgV1FRAcDll1/OLbfcMgUzP7aMtI6lpaWcfvrp5OXlAXD++eezZs0aPvjBD8r7zDDGuo4Hd4vlfWawsa5jIBAY9/uM7CAfx9rb2wGwLIv//d//TZ/G7ujowDRNAHbv3s2OHTsoLy+nuLiYYDDISy+9hG3b/P73v+fiiy+esvkfK8a6jgBf+9rX6Ovr48c//vGUzPlYNNZ1/NSnPkVzczN79+7lueeeY/bs2W/74BjGvo6KonDhhRem127VqlXU1tZOydyPJWNdx2nTprFlyxY6OjoAePzxx6mpqZmayR9DRlrHc889lw0bNhCNRjEMg6effpra2lp5nxnBWNcR5H1mOGNdxyN6nxlf2rSYbFdccYVdVFRkOxwOe9q0afavf/1r+8c//rFdVVVlV1VV2dddd106cf1vf/ubXVtba8+bN89euHCh/c9//jN9nVdffdWuq6uzy8vL7c985jPpx7xdTMQ6NjQ02IBdXV1tz58/354/f759xx13TOXLmnQT9e/xoNEeiHyrmah13Lt3r33qqafa9fX19jve8Q573759U/WSpsREreNtt91mV1dX2/X19fYFF1xgd3Z2TtVLmhJjWUfbtu0//OEPdm1trV1XV2d/+ctfTt8u7zNHvo7yPjNx/x4PGuv7jLSaFkIIIYQQYgBJsRBCCCGEEGIACZCFEEIIIYQYQAJkIYQQQgghBpAAWQghhBBCiAEkQBZCCCGEEGIACZCFEOIY1tvbyy9+8QsAmpubueyyy6Z4RkII8dYnZd6EEOIYtnfvXi644AI2bdo01VMRQoi3DWk1LYQQx7Drr7+eXbt2sWDBAqqqqnj99dfZtGkTv/vd77j//vsxTZNNmzZx7bXXkkwm+cMf/oDb7ebhhx8mJyeHXbt28ZnPfIaOjg58Ph933HEH1dXVU/2yhBDimCYpFkIIcQy75ZZbqKioYN26dXzve98bdN+mTZv485//zCuvvMINN9yAz+dj7dq1nHjiifz+978HYOXKlfz0pz9l9erVfP/73+fTn/70VLwMIYQ4rsgOshBCHKfOPPNMgsEgwWCQzMxMLrzwQgDq6+vZsGED4XCYF154gfe+973pxyQSiamarhBCHDckQBZCiOOU2+1O/39VVdN/VlUVwzCwLIusrCzWrVs3RTMUQojjk6RYCCHEMSwYDBIKhcb12IyMDMrKyrj33nsBsG2b9evXT+T0hBDiLUkCZCGEOIbl5uZy8sknM3fuXL785S+P+fF/+tOfuPPOO5k/fz51dXU88MADR2GWQgjx1iJl3oQQQgghhBhAdpCFEEIIIYQYQAJkIYQQQgghBpAAWQghhBBCiAEkQBZCCCGEEGIACZCFEEIIIYQYQAJkIYQQQgghBpAAWQghhBBCiAH+P82NUjUFn7rUAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from kats.models.sarima import SARIMAModel, SARIMAParams\n",
    "warnings.simplefilter(action='ignore')\n",
    "\n",
    "# create SARIMA param class\n",
    "params = SARIMAParams(\n",
    "    p = 2, \n",
    "    d=1, \n",
    "    q=1, \n",
    "    trend = 'ct', \n",
    "    seasonal_order=(1,0,1,12)\n",
    "    )\n",
    "\n",
    "# initiate SARIMA model\n",
    "m = SARIMAModel(data=air_passengers_ts, params=params)\n",
    "\n",
    "# fit SARIMA model\n",
    "m.fit()\n",
    "\n",
    "# generate forecast values\n",
    "fcst = m.predict(\n",
    "    steps=30, \n",
    "    freq=\"MS\",\n",
    "    include_history=True\n",
    "    )\n",
    "\n",
    "# make plot to visualize\n",
    "m.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.2 Prophet\n",
    "Note: This example requires `fbprophet` be installed, for example with `pip install kats[prophet]` or `pip install kats[all]`\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this.\n",
      "INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# import the param and model classes for Prophet model\n",
    "from kats.models.prophet import ProphetModel, ProphetParams\n",
    "\n",
    "# create a model param instance\n",
    "params = ProphetParams(seasonality_mode='multiplicative') # additive mode gives worse results\n",
    "\n",
    "# create a prophet model instance\n",
    "m = ProphetModel(air_passengers_ts, params)\n",
    "\n",
    "# fit model simply by calling m.fit()\n",
    "m.fit()\n",
    "\n",
    "# make prediction for next 30 month\n",
    "fcst = m.predict(steps=30, freq=\"MS\")\n",
    "\n",
    "# plot to visualize\n",
    "m.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.3 Holt-Winters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from kats.models.holtwinters import HoltWintersParams, HoltWintersModel\n",
    "warnings.simplefilter(action='ignore')\n",
    "\n",
    "\n",
    "params = HoltWintersParams(\n",
    "            trend=\"add\",\n",
    "            #damped=False,\n",
    "            seasonal=\"mul\",\n",
    "            seasonal_periods=12,\n",
    "        )\n",
    "m = HoltWintersModel(\n",
    "    data=air_passengers_ts, \n",
    "    params=params)\n",
    "\n",
    "m.fit()\n",
    "fcst = m.predict(steps=30, alpha = 0.1)\n",
    "m.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Forecasting with Ensemble model\n",
    "\n",
    "`KatsEnsemble` is an ensemble forecasting model, which means it allows you to combine several different forecasting models when building a forecast.  When creating an ensemble, you specify the list of models (with parameters) that you wish to include in the ensemble, and then you choose whether to aggregate these forecasts using the median or the weighted average.  Prior to building any forecasts, the model checks for seasonality and if seasonality is detected, it performs an STL decomposition (using either additive or multiplicative decomposition, as specified by the user).  Each of the forecasting models specified to the ensemble model are only applied to the the de-seasonalized components, and after these forecasts are aggregated the result is reseasonalized.\n",
    "\n",
    "When we initialize `KatsEnsemble`, we include a dictionary with the following components:  \n",
    "\n",
    "* **models:** `EnsembleParams`, contains a list of parameters for each of the individual model parameters     \n",
    "* **aggregation:** 'str', either 'median' or 'weightedavg', how to aggregate the individual forecasts to build an ensemble      \n",
    "* **seasonality_length:** int, the length of the seasonality of the time series      \n",
    "* **decomposition_method** str, either  'multiplicative' or 'additive', the type of decomposition of the initial time series"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the example below, we use the `air_passengers` data set to build a median ensemble forecast that combines 6 different forecasting models.  We use the `EnsembleParams` object to define the parameters for each of these models.  Then generating a forecast for this ensemble is straightforward."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from kats.models.ensemble.ensemble import EnsembleParams, BaseModelParams\n",
    "from kats.models.ensemble.kats_ensemble import KatsEnsemble\n",
    "from kats.models import (\n",
    "    arima,\n",
    "    holtwinters,\n",
    "    linear_model,\n",
    "    prophet,  # requires fbprophet be installed\n",
    "    quadratic_model,\n",
    "    sarima,\n",
    "    theta,\n",
    ")\n",
    "\n",
    "# we need define params for each individual forecasting model in `EnsembleParams` class\n",
    "# here we include 6 different models\n",
    "model_params = EnsembleParams(\n",
    "            [\n",
    "                BaseModelParams(\"arima\", arima.ARIMAParams(p=1, d=1, q=1)),\n",
    "                BaseModelParams(\n",
    "                    \"sarima\",\n",
    "                    sarima.SARIMAParams(\n",
    "                        p=2,\n",
    "                        d=1,\n",
    "                        q=1,\n",
    "                        trend=\"ct\",\n",
    "                        seasonal_order=(1, 0, 1, 12),\n",
    "                        enforce_invertibility=False,\n",
    "                        enforce_stationarity=False,\n",
    "                    ),\n",
    "                ),\n",
    "                BaseModelParams(\"prophet\", prophet.ProphetParams()),  # requires fbprophet be installed\n",
    "                BaseModelParams(\"linear\", linear_model.LinearModelParams()),\n",
    "                BaseModelParams(\"quadratic\", quadratic_model.QuadraticModelParams()),\n",
    "                BaseModelParams(\"theta\", theta.ThetaParams(m=12)),\n",
    "            ]\n",
    "        )\n",
    "\n",
    "# create `KatsEnsembleParam` with detailed configurations \n",
    "KatsEnsembleParam = {\n",
    "    \"models\": model_params,\n",
    "    \"aggregation\": \"median\",\n",
    "    \"seasonality_length\": 12,\n",
    "    \"decomposition_method\": \"multiplicative\",\n",
    "}\n",
    "\n",
    "# create `KatsEnsemble` model\n",
    "m = KatsEnsemble(\n",
    "    data=air_passengers_ts, \n",
    "    params=KatsEnsembleParam\n",
    "    )\n",
    "\n",
    "# fit and predict\n",
    "m.fit()\n",
    "\n",
    "# predict for the next 30 steps\n",
    "fcst = m.predict(steps=30)\n",
    "\n",
    "# aggregate individual model results\n",
    "m.aggregate()\n",
    "\n",
    "# plot to visualize\n",
    "m.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. Multivariate Model Forecasting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vector autoregression (VAR) is a multivariable forecasting algorithm that is supported in Kats.  Here, we show show an example of how to use the `VARModel` with the `multi_ts` data set.  We begin by loading the data set into a `TimeSeriesData` and previewing it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "try: # If running on Jupyter\n",
    "    multi_df = pd.read_csv(\"../kats/data/multi_ts.csv\")\n",
    "except FileNotFoundError: # If running on colab\n",
    "    multi_df = pd.read_csv(\"multi_ts.csv\")\n",
    "multi_ts = TimeSeriesData(multi_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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e7Smo2m1doDnv3ZI9orHDlxZQr2vRtiOfFEB5tep7Vzckpw+kc/7u3hzm5DEeL8Gzfb5bFLdOh9z3a9TH5TstHwtrf3E1ZspVy985m5/nPgRDbZmGnUtc71NBEl4zlS7vppE37g8/3O69+KBASpKrZ9Sgt5sd2rCPm76dn+B7w+9uGPq8f0O9zlCpDvS61QW3u1cHuuUQt8YtZVRQzc91gU5u+UZrx0NKIvS7z//njWzigqiyVVyNp7f6wK8PwxvdXQ/zoGegbOWcjw8Ld+/f0XNOTeJOSwns8J0/+t0DSXtg6ZjCOV9RiFnkcs/8nbQTYhRAebFvmyucmFsvRb0u7oN4zhuhPbW9JIue6+5a/Zl1NvgluHcZ3LPEdZvnV/PzIO2IW6k+VKQmuxyoggzfnaxUWbhqjAsAvr/V5ZUUh0rsoWLrTEhKgLMecikAEaVd9eWNk7xfx1mvuaVEsi682u8+KF0RZrwQ0GaTesRNkqnVtuDPVaaS68VZNtbNssvO6h+gSkOI6u7tuWu3g9tmwaVvQIUabtiufKSbKe1P73KXUa4n6nffjXCmjZPc8F37y721pyAa9XM363kV/vUicTe83q3gixpnZLicsIIsDm0txCyA+h7/j0OIAigvVn3nvrYdkvt+A56A1CSY+XLw2yQnOnrIzTrzt+q2Ma43MbKp92n+WTXqB+FlQqu68O6VLqcjkAEUuLv4a39wMxxnveJ678Q/G/9wNbkaZcnDaX6uq2PkZRJCzCLYNtPl8mV93ZaPhO7Xu7o6J5fpKIj4dWAz3NBSIPT/m+tdmffOqY8d2Q+bpkK7IfnrOQ2PcOVLrv8FntgFf53uf45NWJir0ZS0xwVfmZZ96Yb3CmP4LpMxLlUkdmn+qrdnZ9V3bj3Dn+91vaH5sW8bvN4Vnqzh/n1wnqur5/UGYP82d52j8jFDOEQogPJXRoarON2wb/Yzu7Kq2crVB5r/fuBe+OKfnb6kRH8DqEApXR4a93PTqUNFIBLIc5KZQ1a7vSsHkVNPgpxo4x/QpL/rycvU/DzfY5P8f57Zr0KZKq5m2cl63e7KdORULDY/4nxDgrXaBeb5GvRww2GzXjuxpwfc0F5GKrQNQKmA8Ajvx9Tt5IapF33seliS9sK6ia5obn6eryCOVW8P0HJRq753ZRz2R7tcXa8OxbvZuEf2uo6Cvve4m7TfHoMpT3p7rsyyKOqBOg1smeamwPa4yb/9z3rE3bFNfy6ozZKTZE5jbtCj8M/d5Ew3E+pQfOGfOztb/oRK9VyNlWAIj3B36wdj9Dr3x97Nbhis+fknbq/W2JVFySyp4c/zrPkZetzohsNOVqW++7Bf8hkcTihwswEXQIWXcT21gXLO3+HoQTeJI7MIZnoqLPnCDd/VL8LE4h43uSBj0xTXa5ORWjSFHvNbvT07B3a4xP1et0HHK93izDmVbMjJD7fBwZ1w9deuhtX5/4Fbprre6Bkveps1uGMRRJR1w67FlAIofy38EMpXd/VG/FGtEXS73i35ciguqE2TLLbPhZpt8p8MXhCZwzKhkAeVmgwbp7gZT4FIIM9JQ18y9Nx34EBM8M6TXxkZLoE4+UBRt+T48G7zbJYAaTvEvW78ea+Y86Zbu63XbTnv0+9el7cUqGV4dq+Gmi0D2wNTu51bp3LVd26W3KYp8Pllbmiyz53Bfd3mpdVgN2Q34WGX51e7Q96TUoLhWPX2P/Nf6iLTmp/c13ZD3QhJeoq3xXi3znQ9qOc8AQ2z9PAbAxe/7IY3J/3b/9pV0XNd73hBUieKWMkKoNLTgpPQejAW1v7qVqj3MgOj+w1uOGnNz4Fvk5wqIwO2L8i96F4w1evsZv9tm100589qy3RXRyZzCCCYBjwGWPjz2eCfy4vt8+GDc+HdM+HZJvD55acOFxWmjX+4GkrZFWptN8z1WGd+yOXk8B7XQ9NxhJt1l5Nard0+895z718FFbc6cMN3WfW7D/rc5YbLPhvmPlSHvu0W8y5KEaXdDN29m11B3qs+L7qArtUgb9Xbc7LqBzfkXqOFr3fP+B9AWQuT/+sWT+9x86mPh4XDwP9ByiH/cn8PJ7gUg2Ja/ylTyQqg5r4F75+Tv5oquclc4iO7ZUFyU6utW/Zg1feBbY9kL36tW1OpYe+iOX94KRe8BbIHylqIX+96eL4YAa92Pv7vrT45v9bX/epmYzUphOURqjZ0HzZLvgidBbUPxcGnQ9zabYOed1PCN/8JY67Kf/JsQSTtdR+ArQdn/3itNm64ZtUPuT/P/PfdbM++9+R9zrMfdUNPf/yrYBWtk/ZCYmzgEsizMgYu+D+X6H3DRLh7sStSHArOfMjN0L3y84LXUSuIBr1db9jKb/L/HOmpLj80Mwm+bBWXq+vv8kwbJ7vhv7MehlLlst+nVhs3NDjfj6B981TAHs//K6ZKVgBVJcq9cX5yMbx3tivtP+s196YTtyZ/vVPWwtIvIaqn9yU+jHF3lttmhU5eTEmWWZivsBPIs2rUD3avKvgSDBkZsPxrN+X4zR4w8RE3e6Z+VzfNOqqHq6D+zQ1uavLJx66f6N4sC6tmTf8HXW2fOa8XzvnyMuNFSDsK1/3saiOd92+3hMf2efD19e4DpTDllUdjjFu4ObdhvJQk9+HUcpD78MtLZFPoeSss/wqeawrPNoYXW3tf+DpujfsajB4ocL973U6uLlvVBsE5R36ERxRt4JQpPMLltK2bmP/3lT3rXS9WnY7Ht9Xv7gpZ+vO5uPhjqFATOl+T+34DHnPPN+5a9/6Uk41/QLnI4ExwKUQlK4BqfxncvdB1JYaXdsHTpH+4yslv9XZB1f5ob8+5a7lbfTu/CYTthvrXNS8Ft32em2ESyERXrxr1A6wbisivtKMwZgR8d7MbErz4ZV+tqsUw/EMXCFz+Plz9lZv99v2t7phMm6e6HoNWgwr86/itYi1XI2f510VfhX9/tMtZ7HLNiTc97Ya5pPcNv8GPdx1PXC4My8a64ZPc8mjyeq9Y+oWb/dTPj96nTBc85SqUn/0YtB/uqnF/dyts8FC4M9o3JF0UOUDidLrKBeCZpXS82rXSfa3T/vi2qG6uJtm+Lbkfm3UWYl5V6Ks1hss/cIHZuOuyX64nI8P1aDU7p1iuf5dVyQqgwHUv9rkTbvodnoiFx3bAvcvhohfcePZ7A7ytKr9sbP6X+AA3jFejpfe7PvEueq4bvivK5NP63dxspS3T83d8Rjp8/1c3pf3CZ93QRvcbs78TrtUGLnoeNk+DTy51PReHE+DHO93SMnnVKwu0Hje6vKvlRVyhfMZLgHHDDSfrcZObfr18rFvyI3ZZ8NuzZ6MrGJjXTVjme0V2w3gZ6a44b/3urnq5v8LC3LDy2Y/A4Bfgup/c62bcKNi/3b/nWPWj69WtVNv/80pg1engegBPrpDur90r3PtS9SwLQWeWD4jJIw9q1ffeZiG2vdSVONk4Kfu8yN0r4HBcsR++g5IYQGUVUQbKVHQz4nreAjdPdj9/fpl/Sx0c2edesC0HugJ1+WGMm/GwbZbLZZHgOBTn7qSKcvgOXH2fpme7iQP5GTKe8ZJ7wzr/SZdIG5bHn2jXUa5XKnYZvNQW3u3v7iqHfwSlK+TrV8i3el3dUMzCj4quOnnyARfAdbzCDeln58yHXF7UruUuwfy7W733THuxYpyry9Thitz3y20Yb9X3rjBmv3sKdoNQtoqrJJ+R5l/piT0b3Qde26H5P6cUnDEugIlZ4K3gaqZdK93EgqyzKGu1dT3cO/LoUFg21u2bdfgvL91vcMN9058/8WbSWpj9BmAKtyhpkJTsAOpkNVvCtT+5SsCfDct+1e6spvyfK9/f/28FO2+Xa9win4s+KtjzSM5CIf8pU7thrjaSl55OcD2k0593H1ZehmnaXw63TnVVqSvWdnd/dT282QWKMa63LG6VS1gtCsvHuVUAuudSr80Ylxd1z1I3C2z1j/DuWcErerv2V9drlNusuUzZDeOlp8LUp1wPRGs/y6jkpmpDd338Sfpf7ZsAU9i9mXKqDle4QDw/vVC7V7pSDFmFR7ibnu3zcz4ubi3EzHfJ4V4D94uecz3hX4yAyU/Ctjkw8VF3Q3H2oyWiR/P0CqDA9UaN+t7NqvvgvJyL1+1YBAtGuyTMep0Lds6KtVz9qKVflOyVtYvS1lkuMA6FpMRWg1zAvPoH/4+x1i18Gl4aLnzG+zlrtYELnnSBVNdR3o8PlDaXggl3QUNhs9b9zdbr4l8RxnJVXSHAv053OWTf3VKwtb2ysz/a9eD4m492bObuD8e3LR3jgutz/p53j6S/+j/gihhO/nfuvYWZw3dVglSMVfxXua7r3V4+1lv+XuJuOByffcHKxv3cUjE5FdSc/bp7X+2Sj/eU0hXckk+tB7u1GT+60C3d0+MWV2i6BDj9Aihw03FvnQbVm8LYq12EnHVIL3EXfHOju5sf8ERgztn9Rje8sKIAU1ElZ9tmuerjeSU5FoZyVV339Kof/B/KWvOzyxkY8Lh7oyyuykdCo76BqZzs1fZ5bsJH9xu9HVezFVz8knsNeV2OIi/rfEtw+FuPyxjX07B1Bkx5yiXbTn3KzboM5KSAirVcELXmZ7fOW3Yyg782lwbuvFIwnUa6/5foOf4fs3uF+5o1gTxTk7Ncj2d2pVcOxrrh8K6joEL1/LW3ShQMHw13zncdFzf+DoOeK9o81QA6PQMocP+xN/4O5/3HJR+/0w9+uMOVPPj8cld24KoxbuHUQGh8hhtDnvECpKUE5jnFObLfLSDcqF9Rt+S4zGG8zdPy3vfoIde1XbuD6/Es7loNcsN4gVzM1h8rvnZ3y+0u835sp6vcygEzX4Z57wauTevGu8RwLyVQzrjPlz/ynMvXjCjjJsEE+kPnjPtd9fzxD8KeDac+vtX3oVrMix2WKK0Hu/puy8b4f0zmDLza2QRQUT1cHtTmP099bN7bbqSmz535a2tWNVu5m8qGvQLXixoCSs5vkh+lyro3q3uXQu873Bvwr39zSXpXfhbYVaKNgXP/6T5UlnwWuOfNy7Y5rjft5Q5udtbBnYV37sISPRewoRVAtbkEqjaCn+7Ou/r1n8/AwR2uF6SwFysNhsyekszel8KQkQ6rf4IW57uJIvlx0YvQ+mK3fMfctwueCJ98wC1/4bUafEQZGPIGXPq6S3a/a2HB0wiyExYOl73nzpddWYdts6BsVTesKKGhdAXoMNzVJvS3l3f3SrceZnYToSJKu/y8LScFUMkH3WSQtkNCoxZWiDq9A6hM5SNh4FPwyFZ4aBM8vCn79aoKqvl57sX653OFs3r9kX3w5ZWuF6R2W5dg+3r3wpm6nZ29m12OSqArs2+b5XKHokJoVe8yFd1MuMRYF0Tl9GGcuMv1eHS+puiWoAm0yKZQs7XrfSks0XPc1Oj8lhsBF7xePtoFURMfha+ugd//4XKQsqtnk5eNf7jZbvlZTscY6HqtS3YPZjHUKvXh/P+6NSRPHsrbNssNx5agHoMS4YKnXED99fUw8XGY9mzuN2m7Vmbf+5Sp6VluFYfEXce3Lf7ELfTsT8X705j+MrIqXQEq1Aje9G9j3JDh4ThXqTXYQ3mzX3d3wdf+6Iou3jnfTWP++oaCL0zp1aof4LUuMP4B94e/1EMXdF62zXL1l3JaYqCoRHWDc/7h8kxyWg9x3jvuQ7b/A4XbtmBrPdgNAZ1cJT1YVn3vhu9aDizY85QqCyM+c0mum/90we0Pt8PbvrwuL71S6ya4wq6hFNhnp/M1LlF80j+Or5hwMNbd8IRSr644ZSrC1V+7oGjhhzDtf/D97dm/NtOOuirk2eU/ZWpylvuamW6QlgJz3oLG/f2bjHEaUwBV2Br2gkteg02T3RtzsKohJ+52wxDtLz9eQTiyiatgvW+Lu8MuTLNfc7OL7pjncip+vMvdoRdU0l7YuTR03+j73OVymyY+emqv49FEWPChG+7zukxQqOt4pcufKMj6Xf7KHL5reUFgbn7Cwlwy/+Mx8Pfdbi00mw5fXgUfX+yKleYlPRU2/A4tLwz9asthYa7afcphGHOFe11mJhU3DtG/q9Ndhepwy2T4+y5XcHf9hOxz9+LXutdubj1QdTq60hYzX3Gv22VfQuJO6Hdv0JpfUiiAKgpdR7m1uVZ+49Y4C0bRwfnvQloynP34idsbn+GmkS4bm/PU1UDbudSVhehxsyvmduXnrj7Irw/nb2gkq1W+khRtQ3SmUHiEy206uAOm/u/ExxZ+5BY/7lsC36hqtnI1ZnKa4eWPtKMuHzGvv481P7le3Q4j8n+unBjjAtw75rr6WjEL4Ifb8m7Tttmu97cwl9MpiNrtYMSnELvcVbVfMBpKVzq1dpCEnl5/desjTvoH7Nt24mPHlnDJ5f8xLMzNjItf4/JkJzzseiRLQKXwYFMAVVT63ed6J+a/51ZLD2RPlLWw8jtocibUaH7q4+0vd8NGgegB8seij9zwSqcr3c9lKrkAcu8mb7NJspOfKrmFrUFPV7hw7ptuWjq4HsLpL7iZKYGcrBBKOo10syMz38T9lfn6faMHvN4VPrnEBeA57TvrVZd3FcxgJbyUWwZm4FOuZ2nOm7nvv26Cq7PUbEDw2hRoLQe6HurD8W79uyZnloxJDSWdMW6ZHozLr81q90r33pvX+qCtBrlcveVfud6oq74sMaUGgsmvAMoYs9UYs8IYs9QYs9C3LdIYM8kYs8H3tVpwm1rCGOOW6+h+o/sA+OovgUss37XcDdPllFAb1d2trF0YtXqOJroFZttfDuWyvERaDXJ5S9OegdTk/D13wiZXJbfTVaH/x37B/0HNNm6dux2L4PcnIO2Im2VVUrW/HMIivK2Nl5YCP98D39wAZSq7RXDj1sD757jcve3zT+y13DoTdi5xNyOFMVTW42aXZD75v3AgJvt9rHUJ9E3PLvzldAqq/eVw3wq4ezEMfauoWyP+qhLlXpvLxpy4ZNiuFW4CkT9/G4NfdJ9Ho77Pf92n04yXHqgB1trO1trMjMhHgcnW2hbAZN/P4kVYmBsWGPQcrJ8Iv9wXmOG8VT+4atA5LfsQFu7uNjdMcmPewbRxsltgtvPIE7cbA+f+yw1t/XhH/nrgln8FmLzXGAsFpcvDFR+5SvTvn+NKZvS7N/sewpKiQnVv6wJa624kFn8K/R+Ev/7plny4Z4lbv279RBh9PjzfzN1pb5nuhhvK14DOVwf91wHc6/bCpwF76t1+pi3TXbHDgswILErGuJy8clWLuiXiRf8HXE2niY+4mwxrfUu45JL/lFXlei4XLqc1JOUUBRnCGwJ84vv+E2BogVtzOjLGjWGf/bj7UC3o7DRr3RIiTfrnfhfR6iKXf7NtdsHOl5d1E1zPU4Pepz7W9Cw3K3Hlt67+lpcg6nCCG/5sfp77wy8OarVx668Ne9fN8ur/YFG3KPhaXeR6Q+PX5b3viq/d8NjAp13NtMy75rKV3TIm969ypSEa9XPVuT+5xC2cPOSNwp2BWbWhu1Nf8nn2C7suHO1e81qAVwpThRpuOadNU1wv7r4trrxBbvlPUiD+BlAW+N0Ys8gYk1kquba1Ntb3/S6g+K8MWJT6P+Cmjf76t4JN/Y5d5qYf5/Xm3XSAy9FYH8Rih+lpsOE3aDEw51yKfve6WiMLR7u6O/6WV/jjn27fCwK89EawVazphhwHPB56ZReCoeWF7uu6PNbGO7IffnvCDev2ui37fcpHQvvLYOQYt4rAJa+53qmiSNTu/6Crz/THv0/cnrjLra/Z+S+uJIJIYep+I5z1qFt39TXfuqAKoILG3wDqDGttV2AQcKcx5sysD1prLS7IOoUx5lZjzEJjzML4+PiCtbYkCwuHS151Qzzz3sn/8ywf5xayzWv19NLloX53t35YsGyf6+6AcvuAM8YV8rvwWRfMvdnbJYbn1hu1daa7++9zp+vVkdBVpT7U7Zx3vt2U/4OkPW5I25/CjQ17Qbfrii7HqGItOOMBNwMw62SMhR+6CRpe1+MTCZSzH3UFYc/7txuSiyohBXpDkF8BlLV2h+9rHPA90BPYbYypC+D7GpfDse9Za7tba7vXrFkzMK0uqao3c1OmF47OX6HL9DRYMQ5aXZh92f6TRXVzSYZpR72fyx/rJrgK4XlVdTcGet8G1493w47f/xXePRPW/35qmYO4ta6nKrIpnPlwcNotgdV6sJv+fyjbtwiXBL7gA1deIxhLlgRLv3sgshmM/5tb+mLteJj+vFt8t6TV9ZLiwxi33MsZ97tAXpXkgybPK2uMqWCMqZT5PXABsBL4CbjOt9t1wI/BauRppd+9rn7M4nysl7dpipuC3Glk3vuC64FKT3FBVDCsm+DqTpWp5N/+jfrALdPc3dPRA66o33NNXcC04AO3ZMGnQ1xQds13+V/zTApXq4sA65aHOFlGOvxyv+vROeeJQm9agUSUcTOX9m1xr9Nx10G9LjD07aJumYgUAn+KfNQGvjdumngEMMZaO9EYswAYZ4y5CdgGBKGK3Wkoqjs07OvqzPS8xdWf8deyL6FcJDQ/3/9zAcQsDPxyE3s3uzpPPW/Ne9+swsLc3VObS1zezKYpsHGKbykU43JkLnnVVVWX4qFOe/f/Of1FV+yyWqPjj81+zfVAXT7aLTNU3DQbADf+Bmt/gQM74KIXFNiLnCbyDKCstZuBTtlsTwCCsOKu0O9etwjwqu+ho59xadJeN4TQ7Tq3wrY/KteDSvXc8Ao5JO7mV2bByPxWs40o46aBtxvmZhbu2+JWhvdnaFJCz4XPwMaeruzAyLFumGH7fJj8pPs/bn95Ubcw/xr2dv9E5LSiwdFQ1OICqNEKZr3mf12opWMg/Sh0vS7vfbOK6gY7FnpvY142ToZqjQOTC2KMy3lS8FR8VYlyMw/XT3SLSS8b64Zmq9R3PYqhXghVROQkCqBCUVgY9L0bdq9wiw7nxVo3+6dBr9xX3c5OVA/YtxUO7/HezpyKcKYddcUEm5+nD0Y5rs+driL7mp/cRIGKtdySEcVx6E5ETnsKoEJVxxFQpeHxGT652fKnyzfqfpP389T35T5tn+/f/ilJMOFReKUjPNvE5U+dLHqOqz6uxSglK2PcjcF1P8MVH8Ot070H/CIiIUIBVKiKKAOXvQf7t8H4B3IeystIhz+f91U+zqP2U3bqd3Pl/zdPzXvf9FQYdy3Mf9et3l6hOnwx3JUWyCqzfEHj/t7bIyVf4zNc3pOmV4tIMaZ3sFDWqM/xJV7GP5j9kNnMl2DbTFeMMj+Vj0uVdYFO1mKAORn/AGyc5IqzjfwSRv3gAqWvrjleryn1iJsN2PpizUYSEZESy58yBlKU+j8IRw+66d47FrrZSpHNXMJ49FxYMBraD4cuo/J/jubnuSVXEjblnPS9b6urTdX7Duh2vdsW2cRVjv7qLy5o6jrKzRxMPqBKzCIiUqIpgAp1YWFuvbe6nWD6CzDpn8cfiygHrS9yPUIFSdZucR5MwM2cyymAWvSJO0efO0/c3now1OsKfz7r8rYWfgjVW7hhGhERkRJKAVRx0WG4+5e4Cw7tBhPmApVALFga2dT92/gH9Mqm8GVaCiz5zC0MWyXqxMeMgXP/CZ8NhRdbw5G9MPBpzb4TEZESTQFUcVOpjvsXaM3Pc0N0qcmnBmVrf3FLxOQ0y6/p2S4Ha+9mKFUBul4b+PaJiIiEEAVQ4rQcCPPfc/WbWl5w4mMLP4SqDaHZOdkfa4yrni4iInKa0Cw8cRr3h9IV3fpzWcWvh60zoNsNmnYuIiLio09EcSLKQPNzXQ2njIzj2xd9BGGlCjbLT0REpIRRACXHtRoMh3ZB7BL3c+oRWPoFtL0UKtYs2raJiIiEEAVQclyL88GEw5pfXOXziY/5ajrlY4kYERGREkxJ5HJc+Ug3o27myy7vKWYBnHE/NO5X1C0TEREJKeqBkhMN/9At+Bq73FUcP/dfRd0iERGRkKMeKDlRuaqu8vmAxyGirApiioiIZEMBlGSvVLmiboGIiEjI0hCeiIiIiEcKoEREREQ8UgAlIiIi4pECKBERERGPFECJiIiIeKQASkRERMQjBVAiIiIiHimAEhEREfFIAZSIiIiIRwqgRERERDxSACUiIiLikQIoEREREY8UQImIiIh4pABKRERExCMFUCIiIiIeKYASERER8UgBlIiIiIhHCqBEREREPFIAJSIiIuKRAigRERERj/wOoIwx4caYJcaYX3w/NzHGzDPGbDTGfGWMKR28ZoqIiIiEDi89UPcCa7L8/CzwsrW2ObAPuCmQDRMREREJVX4FUMaYKGAw8IHvZwOcA3zj2+UTYGgQ2iciIiIScvztgXoFeBjI8P1cHdhvrU3z/RwD1A9s00RERERCU54BlDHmYiDOWrsoPycwxtxqjFlojFkYHx+fn6cQERERCSn+9ED1Ay41xmwFxuKG7l4FqhpjInz7RAE7sjvYWvuetba7tbZ7zZo1A9BkERERkaKVZwBlrX3MWhtlrW0MXAVMsdb+BZgKDPftdh3wY9BaKSIiIhJCClIH6hHgAWPMRlxO1OjANElEREQktEXkvctx1tppwDTf95uBnoFvkoiIiEhoUyVyEREREY8UQImIiIh4pABKRERExCMFUCIiIiIeKYASERER8UgBlIiIiIhHCqBEREREPFIAJSIiIuKRAigRERERjxRAiYiIiHikAEpERETEIwVQIiIiIh4pgBIRERHxSAGUiIiIiEcKoEREREQ8UgAlIiIi4pECKBERERGPFECJiIiIeKQASkRERMQjBVAiIiIiHimAEhEREfFIAZSIiIiIRwqgRERERDxSACUiIiLikQIoEREREY8UQImIiIh4pABKRERExCMFUCIiIiIeKYASERER8UgBlIiIiIhHEUXdABERESneUlNTiYmJITk5uaibki9ly5YlKiqKUqVK+X2MAigREREpkJiYGCpVqkTjxo0xxhR1czyx1pKQkEBMTAxNmjTx+zgN4YmIiEiBJCcnU7169WIXPAEYY6hevbrn3jMFUCIiIlJgxTF4ypSftiuAEhEREfFIAZSIiIgUawMGDOC33347Ydsrr7zC7bffzoUXXkjVqlW5+OKLA3pOBVAiIiJSrI0cOZKxY8eesG3s2LGMHDmShx56iM8++yzg51QAJSIiIsXa8OHDGT9+PCkpKQBs3bqVnTt30r9/f84991wqVaoU8HPmWcbAGFMWmA6U8e3/jbX2X8aYJsBYoDqwCBhlrU0JeAtFRESk2PjPz6tYvfNgQJ+zbb3K/OuSdjk+HhkZSc+ePZkwYQJDhgxh7NixjBgxIqiJ7f70QB0FzrHWdgI6AxcaY3oDzwIvW2ubA/uAm4LWShEREZFcZB3Gyxy+C6Y8e6CstRY45PuxlO+fBc4BrvZt/wT4N/B24JsoIiIixUVuPUXBNGTIEO6//34WL15MUlIS3bp1C+r5/MqBMsaEG2OWAnHAJGATsN9am+bbJQaoH5QWioiIiOShYsWKDBgwgBtvvDHovU/gZwBlrU231nYGooCeQGt/T2CMudUYs9AYszA+Pj5/rRQRERHJw8iRI1m2bNkJAVT//v254oormDx5MlFRUaeUO8gvT2vhWWv3G2OmAn2AqsaYCF8vVBSwI4dj3gPeA+jevbstYHtFREREsjV06FBc5tFxM2bMCMq58uyBMsbUNMZU9X1fDjgfWANMBYb7drsO+DEoLRQREREJMf70QNUFPjHGhOMCrnHW2l+MMauBscaY/wOWAKOD2E4RERGRkOHPLLzlQJdstm/G5UOJiIiInFZUiVxERETEIwVQIiIiIh4pgBIRERHxSAGUiIiIFGsDBgw4pb7TK6+8wqBBg+jTpw/t2rWjY8eOfPXVVwE7p6c6UCIiIiKhJnMdvIEDBx7bNnbsWJ577jnq1q1LixYt2LlzJ926dWPgwIFUrVq1wOdUD5SIiIgUa8OHD2f8+PGkpKQAsHXrVnbu3En//v1p0aIFAPXq1aNWrVoEalUU9UCJiIhI4Ex4FHatCOxz1ukAg57J8eHIyEh69uzJhAkTGDJkCGPHjmXEiBEYY47tM3/+fFJSUmjWrFlAmqQeKBERESn2MofxwA3fZV0PLzY2llGjRvHRRx8RFhaY0Ec9UCIiIhI4ufQUBdOQIUO4//77Wbx4MUlJSXTr1g2AgwcPMnjwYJ566il69+4dsPOpB0pERESKvYoVKzJgwABuvPHGY71PKSkpDBs2jGuvvZbhw4fn8QzeKIASERGREmHkyJEsW7bsWAA1btw4pk+fzscff0znzp3p3LkzS5cuDci5NIQnIiIiJcLQoUOx1h77+ZprruGaa64JyrnUAyUiIiLikQIoEREREY8UQImIiEiBZR06K27y03YFUCIiIlIgZcuWJSEhoVgGUdZaEhISKFu2rKfjlEQuIiIiBRIVFUVMTEzAlkkpbGXLliUqKsrTMQqgREREpEBKlSpFkyZNiroZhUpDeCIiIiIeKYASERER8UgBlIiIiIhHCqBEREREPFIAJSIiIuKRAigRERERjxRAiYiIiHikAEpERETEIwVQIiIiIh4pgBIRERHxSAGUiIiIiEcKoEREREQ8UgAlIiIi4pECKBERERGPFECJiIiIeKQASkRERMQjBVAiIiIiHimAEhEREfFIAZSIiIiIRwqgRERERDzKM4AyxjQwxkw1xqw2xqwyxtzr2x5pjJlkjNng+1ot+M0VERERKXr+9EClAQ9aa9sCvYE7jTFtgUeBydbaFsBk388iIiIiJV6eAZS1NtZau9j3fSKwBqgPDAE+8e32CTA0SG0UERERCSmecqCMMY2BLsA8oLa1Ntb30C6gdg7H3GqMWWiMWRgfH1+QtoqIiIiEBL8DKGNMReBb4D5r7cGsj1lrLWCzO85a+561tru1tnvNmjUL1FgRERGRUOBXAGWMKYULnr6w1n7n27zbGFPX93hdIC44TRQREREJLf7MwjPAaGCNtfalLA/9BFzn+/464MfAN09EREQk9ET4sU8/YBSwwhiz1LftceAZYJwx5iZgGzAiKC0UERERCTF5BlDW2pmAyeHhcwPbHBEREZHQp0rkIiIiIh4pgBIRERHxSAGUiIiIiEcKoEREREQ8UgAlIiIi4pECKBERERGPFECJiIiIeKQASkRERMQjBVAiIiIiHimAEhEREfFIAZSIiIiIRwqgRERERDxSACUiIiLikQIoEREREY8UQImIiIh4pABKRERExCMFUCIiIiIeKYASERER8UgBlIiIiIhHCqBEREREPFIAJSIiIuKRAigRERERjxRAiYiIiHikAEpERETEIwVQIiIiIh4pgBIRERHxSAGUiIiIiEcKoEREREQ8UgAlIiIi4pECKBERERGPFECJiIiIeKQASkRERMQjBVAiIiIiHimAEhEREfFIAZSIiIiIRwqgRERERDxSACUiIiLikQIoEREREY/yDKCMMR8aY+KMMSuzbIs0xkwyxmzwfa0W3GaKiIiIhA5/eqA+Bi48adujwGRrbQtgsu9nERERkdNCngGUtXY6sPekzUOAT3zffwIMDWyzREREREJXfnOgaltrY33f7wJq57SjMeZWY8xCY8zC+Pj4fJ5OREREJHQUOIncWmsBm8vj71lru1tru9esWbOgpxMREREpcvkNoHYbY+oC+L7GBa5JIiIiIqEtvwHUT8B1vu+vA34MTHNEREREQp8/ZQy+BOYArYwxMcaYm4BngPONMRuA83w/i4iIiJwWIvLawVo7MoeHzg1wW0RERESKBVUiFxEREfFIAZSIiIiIRwqgRERERDxSACUiIiLikQIoEREREY8UQImIiIh4pABKRERExCMFUCIiIiIeKYASERER8UgBlIiIiIhHCqBEREREPFIAJSIiIuKRAigRERERjxRAiYiIiHikAEpERETEIwVQIiIiIh4pgBIRERHxSAGUiIiIiEcKoEREREQ8UgAlIiIi4pECKBERERGPFECJiIiIeKQASkRERMQjBVAiIiIiHimAEhEREfFIAZSIiIiIRwqgRERERDyKKOoGSOHaGJfIh7O2smrnQSqXjWB4tyiGdK5f1M0SEREpVhRAnUbmbk5g5PtzKR0eRvfG1dix/wj3jl1KdEISd53THGNMUTdRRESkWFAAdRr5cekOKpSOYNpDZ1OjYhlS0jJ45NvlvDhpPdUqlOaa3o2KuokiIiLFgnKgThPWWqaujad/ixrUqFgGgNIRYbx4RSf6t6jB07+uIWZfUhG3UkREpHhQD1QRs9YyfcMePpy5hVLhYTSILEfrOpVoWrMitSqVoV7VcpQKL3icuyY2kV0HkxnQutYJ28PCDE9f1oGBL0/n0W9X8OmNPQkLy34ob/Ka3Xw5fzsLtu5lYLva/G1gK2pVKlvgtomIiBQ3CqCKUEaG5e6xSxi/PJZ6VcpSuVwpZm/aQ1JK+rF9SoUbWtauxGVdoxjRPYpKZUvl61xT18UBcHarmqc8FlWtPH+/uC2PfbeClyat528DW53weFp6Bs9OXMv7M7ZQp3JZ+jarzvdLdvDHmjimPXQ2lfPZJilZDian8suyWGZt2kNUtXL0aBTJuW1qKbdOREokBVBFaPTMLYxfHss957bgrgHNKR0RRkaGJXpvEtv2JhF3MJlN8YeZuzmBJ39ZzdvTNvLxDT1pX7+K53NNXRtHh/pVcuwxuqpHA5bH7OeNqRtpUqMCl3eLAiA1PYO7xizmt1W7ubZPI/5xcVtKhYcxfX081344n5kb9nBRh7oFug5S/M3ZlMBtny/iwJFUalcuw6RVqbz752Y6RlXhf8M65Os1GyqSU9OZszmBOpXL0rpOJQWEIgIogCoyy7bv57nf1jKwXW3uP6/FsTflsDBD4xoVaFyjwgn7L92+nzu/WMzI9+by0Q096N440u9zLd2+n8XR+7hrQPMc9zHG8J9L27Nlz2Ee/HoZK3ce4NzWtfl0zlZ+X72bf17clhvPaHJs/77NqlO5bATT1sUVOIBKOHSUlTsPEp94lOoVStOzSSQVyhTvl2Z6hmXv4RRqVCxd4j9wxy+P5f6vltKwenk+vqEHnRtUJS3D8uPSnTz/21qu/2gBv957RrEb7rXW8urkDbw/fTOHfb3CDSPd79i0ZsUibp2crg4cSWVJ9D4OJqfRp2l1alYqU9RNOm0Za22hnax79+524cKFhXa+UJSRYfluyQ7+8cNKqpUvxfh7+lOtQmm/jt25/wjXfDCPfUkp/HJPf+pXLZfnMbsPJnPJ6zMpHRHGT3edQWQe5zqals7Tv67l49lbj207OXjKdOcXi1mwdS/zHj831yBhxoZ4vlu8g7mbE0hOTadMRDh1q5aldHgYB46ksnZX4gn7lwo3XNenMX8b2IqypcLz/B1DgbWWmH1HmLI2jp+X7WTFjgMcTcugdZ1K3NivCSN6NCjqJgbFwq17Gfn+XDpFVWX0dT2oUv7E4dz1uxO59I2ZdGtUjU9v7EV4Dvl1WVlr2b73CGFhUKNimSJ7Dbzz5yaemeBuckb2bEjcwaM89esaWtauyFe39skxV1AkWBZs3ctdYxaz++BRABpVL8/3d/TL8X3dWsuqnQc5kppO90bVSvzNXDAYYxZZa7tn+5gCqODYvjeJmRv3sCb2IEkp6SSnpnP4aBrLYg6w93AKvZpE8vrILtSq7O2ufHP8IS59YxbNalVk3F97UyYi5w+XXQeSueHjBWxLOMx3d/SldZ3Kfp9n1c4DHD6aTt0qZWkQWT7bfb5euJ2HvlnO+HvOoF29U4dorLW88scGXp28gSrlSnFWy5pUKVeKpJR0Yg8cIT3DUq50ON0bVaNH40jqVClLzL4j/LBkB18viqFpjQq8dU1XT+0uLHGJyXw2ZxvfLd7B0bR0UtMtB46kAtC6TiXOaF6D6hXL8MvynazaeZCnL+vAyJ4Ni7jVgRWzL4khb8yiUtkIfrizH1XLZ/8m/tWCaB75dgUjukfx9GUdcwyilm3fz+dztzF1XTx7DrkPiNLhYQzvHsWdA5r7dcMQCOkZljenbuSlSeu5pFM9Xr2y87FgadzC7Tz8zXKeHNKOUX0aF0p7AiHh0FEWbdvH6tiDrIk9yK4DyTSILM+g9nUZ3FFD8MXBVwuiefz7lURVK8d/h7QnLT2DO75YTPv6Vfji5l6n3GisiDnAXz9byM4DyYB7X3picBv6tzg1D1ZypgCqkH0+dxv/+HEl1kKlshFUKhNB2VLhlCkVTps6lejfsgaXdKxHRD5n101YEcvtXyzmim5RPDe8Y7Z3Fat2HuCmjxeSmJzK29d048yWgf+jiUtMpudTk3loYCvuzGZ48LmJa3lr2iaGd4viqWHtcw32TjZr4x7u/2oph46m8eIVnRgUQnlWaekZXPDKdLbsOczZLWtSz/fB3rpuZXo1iaRl7UrH9k3PsFz/0Xzmbd7Ll7f2plujakXV7IA6cCSVK96ZTez+ZL6/sx/Na+U8pGWt5eU/NvDa5A2c07oWQ7vUp37VslgLsQeSWR17kD9W72ZD3CEqlA7nvLa16dE4klLhhqXb9/PNohgqlIlg3F/7nHBt8+toWjqx+5M5kppOeobFWkhJTycxOY0Nuw/x68pYlkTvZ0jnejw/vBOlI47/nVprGTV6Pkui9zHpgbOO/d97EZ94lDmbE9ix7wiDO9SlYfXsb1ACITU9g49nbeXlP9aTlJKOMdC4egXqVS3LprjD7E5M5v1R3Tmvbe2gtUHyZq3lnT83M2dzAgmHjtKpQVXOalmTfs1rkJ5h+XT2Vl6ctJ7+LWrw5l+6Hpu4M355LHeOWcwjF7bm9rObHXu+5NR0Br82g8NH0/nbwFZkWMs70zYRvTeJF67oxNAuWn3CX0ELoIwxFwKvAuHAB9baZ3LbvygCKGstOw8ks/tgMtsSDrM2NpE9h1JITc+gR5NIBrat7bkXKLdzvTVtE8//to5zWtfiicFtaFqjQlC6TV/6fR2vTdnIwxe24o6zTwxeJq/Zzd1fLqFKuVJ8eH0P2tQNXg/Oxa/P4EhKOj/edQYVs+Qt/b5qF7d+toirejTgf8M65Gu4I+5gMrd9vogl2/fzwvBOxxLbi9r3S2K4/6tlvPWXrn7lf+1PSuGSN2YSERbG7/efWeCyFGnpGYSHmSLrjk9Jy+D6j+azYOtePrmhJ32b1/DruA9mbOa539aRkpZxwvbwMEPPxpFc1KEOQ7vUP2Wm6eb4Q1z53lwM8O3tfXPsEc3Lyh0HePKX1czfupfc3vaiqpXj/vNaclnX+tle4+17k7jg5en0aVad0dd19/T/sHrnQS57exbJqe4aGAOXd43i6cs6BKRcSVZJKWnc+ukiZm7cw7mta3H72c1oU7fysfzCIynpjHh3DpvjD/HDnf1oEYDgVPLnw5lb+O8vq2ldpxI1K5Vh8bZ9HE5Jp1S4IcO6G7GLO9blpRGdTwjoAa77cD7LY/Yz45Fzjr0H/98vq/lg5hY+v6kXZ7Rwf5+Jyanc+uki5mxO4JUrOyuI8lNQAihjTDiwHjgfiAEWACOttatzOqYwA6j0DMvElbt4d/omlsccOLa9dEQYNSuWIcNaYg8kUzo8jNvOasodA5oXKNfCWsszE9by7vTNDO1cj+ev6BTwN8STz3fP2KX8vGwnV/VowGOD2lCmVBgv/7Ge96dvpm29yoy+rge1AxQc5mTaujhu+mQh/ZrXYPR13SkVHkbMviQufn0m9auW47s7+nrqeTrZkZR0bvl0IbM27eG1q7pwSad6AWy9d+kZlgte/pNS4WH8ek9/vwPDyWt2c9MnC/M99GOtZdzC7XwxL5q1sYm0qF2R/xvani4NC7dHy1rLg+OW8d2SHbx4hfegNiUtgw1x7iYGoHblMjSuXiHPv711uxIZ8e4cmtSowLe39/UrlwpcL+mk1bv5bdVuZmyIp1r50ozs2YAmNSpSoXQ4YWGGMGMoFW6oWCaChtXL+5XsPnrmFp78ZTWvXtXZ77Ukk1PTufSNmexLSuW9Ud2oWakMn8zeyvsztnBRhzq8dlWXfPdKn2zXgWTuGrOYxdH7ePqyDozo3iDbQC/2wBEGvzaTdvUq89lNvQJybvFm0bZ9XPnuHAa0rsV7o7phjCElLYNF2/YxfUM8EWGGM1vWzDGHadn2/Qx5c9axkYCPZ23h3z+vZlTvRjw5tP0J+yanpnP9R/NZvG0/Y27p5WkyUm7W707ky/nuvSkpJY2rezXM8TWXE2stczfvZfqGeLbvTaJC6Qha1K5Iy9qVaF23UpFNQglWANUH+Le1dqDv58cArLVP53RMYQRQ0QlJTFqzm0/nbGVbQhKNq5fnmt6NaFqzAlHVytO0RgUiwsOw1rIx7hBvTN3Ij0t30qp2JT64rnu+7m6TUtJ4/LsV/LB0J9f2acS/L2lXKAmmR9PSeWmSC5gyLESEGdIyLFf1aMA/L2lL+dKFM5MtM8elduUytKtXhZkb9hARbvj57jNoFoDZSsmp6YwaPY81sYlMvK8/UdWCN+SRlx+X7uDesUt58+qunnJHrLVc+d5cNscfYtpDA07orctLXGIy//hhJb+t2k37+pXp0TiSCSt2sTsxmVeu9P8DvKCstTz/2zremraJB85vyT3ntiiU82bKvPZ/H9yGm/s3zXG/2ANHGL88lokrd7Eoeh/WumTbizvW5dYzm1GlXMHrlqVnWK54Zzbrdx/ix7v6+fU6z+wV+PiGHpzd6nhB2w9mbOb/xq9hWJf6vHhFJ7/fO6ITknj422Xs2H8EgI5RVWlcvTyJyWl8vTCGdGt55crOefaSZibL/3BnPzo3qOrXufOSlu4CgOi9SVQpV4qmNSvSrGZweuPzI+HQUSas3EWNimXo0bga1SsWzUy25NR0Br4ynQxr+eXu/vl+bd78yQKmr99Dm7qVWBZzgIHtavP6yK6n9FaB6xEf9tZsDh5JZcJ9/fMdmGT+nf28bCfLYg5QOjyMDlFVSEpJZ03sQYZ3i+KZyzr4dVOwcOtenvxlNctiDhARZqhfrRyHktNIOJxybJ+OUVUY1qU+V/dqWKCbcq+CFUANBy601t7s+3kU0Mtae9dJ+90K3ArQsGHDbtu2bcvX+fzxn59X8dGsrQB0alCV285sygXt6uR5tzptXRz3fLmEUuFhfHxDTzpE+V+zZlP8IW7/fBEb4g7xwHkti2RR3hUxB/hzfRwHk9OOjZsXtt9X7eK7xTtYseMA57WpxfX9mtDkpFIMBbF9bxKDXp1BB1/CZFHMgDpwJJXzX/qTGhXL8MvdZ3huw5LofQx7azZdG1blv0PaU6VcKRZH7+PHpTtZtyuR+MSjNIgsR4f6VWhfvwrVK5YmOuEIH8zYzNG0DB4a2IqbzmhCWJghMTmV6z9awPpdiUy8/8ygJ1jHJx7lse+W88eaOK7q0YCnL+tQ6K9zay23fLqQmRv38OOdZ9CqzolDTit3HODlSeuZui6ODAtt6lZmYLvaXNi+Dq1qB75+0879R7jk9ZlUq1CaH+7sl2tQHJ2QxDkvTuMKXyL9yd6YsoEXfl/PzWc04YnBbfJsa1xiMle8M4f9SakMaFWT1HTLkuh97E48SrgxnN+2No8Oau3XDeGho2mc8ewUujWsxujre+T9i+dh9sY93P3lkhM+/AAiK5Tmog51GNmzYbaTTgpDWnoG//t1LZ/P3UZKuhtGLRMRxphbiiY/MTNPdMwtvejbLP/v27sPJvP2tE0sj9lPu3pV+OclbXMdAdmwO5HBr89kQKuavHNNN7//NvYeTmH8ilh+XrqT+Vv3AtC+fmUu7VSPy7tGUb1iGdIzLK/+sZ7XpmzkrgHNTynMnFVKWgb/+3UNn8zZSr0q5bhjQDMu7xp1rEc64dBRNsQdYnH0Pn5buYtlMQeoX7Ucw7rUp0vDqvRsEpnv4tL+KtIAKqtg90DN2BDPht2HOKd1rVPqKOVlU/whrh09n+TUdL69va9fx49fHsvD3yyjdEQYr17VJSiJ2nJcZk/Xy1d2YlgX/4aOrLXM37KX9XGHuKBt7QINaT7yzXK+WRzDj3f2y3dhyB+X7uBfP61if1LqsW31qpSld9Pq1KhUhs3xh1mxY/+xacoA/VvU4D+Xtjul9lB0QhKDXp1Oh6gqjLm5d8CDypS0DKasjePbxTFMXRtHmDE8dlFrru/buMh6EjLLcgB8c1tfGlYvT8Kho7w5dRMfz97iG6JryPBuUZ7fA/Jj9sY9XDN6Hhe2r8ObV3fN8bo8MG4p45fHMv3hAdm+Bq21/Ofn1Xw8eyuPDmrNbWc1y+ZZnJS0DIa/M5sNuw/xxS296BqAYdzXJ2/gxUnr+emufnSMqprv59kYl8iwt2ZTu3JZHji/Je3qVebAkVTWxB5k5sYEfl+1i5T0DG7p35QHL2hZqD0JR1LSuWvMYiavjePK7g24vl9jDh9N496xSykVbhh/T/9CrT+3eudBLn1jJsO61Of5KzoV2nkzZfY8+jMMvWF3Iq9P2cjEle7/r3mtilzaqR4Xd6ybY020R75ZzrhF2/n0xp7ZzvxLTE7l9s8XM3PjHq7t04hHLmyd5/WfsSGeV//YwJLt+0nPsHx3R9+AvP5zc1oN4RXEpvhDDH97NpXLleKHO/rlWp/p/embeerXNXRpWJU3r+6ar9k44k1GhuXCV6cTZgwT7u2f54f4xrhD3PrZQjbHHwZcsvLIng34z6Xt/c6hyfTzsp3c/eUSbjurGY8Oap3v3wFgz6Gj/LoilrIR4TSqXp4ejSNPCX7iEpNJTE4jsnzpXF+HX86P5rHvVvD2X7oGdKbiH6t389j3K4hPPErNSmUY1qU+V/ZoEJAh2YJav9vlQ6VnWFrWrsTqnQdJTkvnqh4NefTC1qfUogq296Zv4n+/ruWxQa35azaBz8a4RC54eTo3ndGEJwa3zfF5MjIs937l8hqfH96RK7pnXzvsxd/X8fqUjbxzTTcubF8nIL9DYnIqA174k4aR5fjmtr75CsaPpLjhqKSUNH64s1+2Q+0HjqTy3MS1fDEvmk4NqvLR9T3yrE2Xlp7B+BWxzNq4h+i9SZQrFU5UtfJ0aViVPs2qU7eKf++9j3+/gi/nR/PfS0/MQ5y7OYGR78/19aye2jsYDInJqQx5YxaHjqbx231n+l0LMJDSMyzD35nNyh0H+Ocl7bimV8NT3lMz00RGz9hCuVLhXN4tiit7NPCrIv+RlHSGvDmTmH1H+O+Q9lzum5RhrWXK2jie/GU1MfuO8PRlHXJ8ref23Ct2HKBTgypBD8KDFUBF4JLIzwV24JLIr7bWrsrpmFAPoAAWR+/jqnfn0qtpJB/f0DPbD9pX/9jAy3+sZ3CHurx0ZadCvYs63WXWnvrkxp6clUuP35Y9h7ny3TlkWMtjg9rQrn5lPp+7jc/nRnsegpqxIZ4bP15AlwbV+PSmniFV3DMzqT3MGCbed6bnwHBT/CE27D7EvqQUwgwcPJLGnM0JTFkbR5u6lXl4YCv6t6gRsOTmQFm98yAfzdrCtoQkGkSW5/azm9K8VtHMIrPWcteYJUxYGcsbV584MzMtPYOr35/Hqp0HmP7wgDxzbVLSMrjpkwXM2riH57OZebokeh/D35nDsC71eSHAvRaZf1v5mRwA8Pa0TTw7ca1fw1ETV8Zy79ilRFUrx2c39crxBnTRtr08OG4ZWxOSqF6hNI1rVCA5NZ3ohCQSj6YB0KtJJKP6NOKi9nVzDPzW707kwlemc22fxvz70nanPP7MhLW88+cmnr28A1f2KFi9tt0Hk/l91S6mrYunQpmIY7k7mf/3aekZ3Dt2KRNX7WLMzb3o1bR6gc5XEAeSUrnvqyVMXRfPgFY1eWRQ62N196ITkrjry8UsjznAiO5RPHJha8+5YrsOJHPv2CXM27KXxtXL07B6BdbvcgvbN6tZgf8b2oE+zYru9/dHMMsYXAS8gitj8KG19qnc9i8OARTA2PnRPPrdimx7G/5YvZubP13IZV3r8/zwTp4/sKRgUtIy6P/cFJrVrMiYW3pnu8+BI6kMfm0GSSnpfHlL7xNyZV74bR1vTN14St2U7FhrGbtgO//+aRVNalTgq7/2CUgCcqD9snwnd41Z4mlG2IqYA7zw+zr+XB9/ymMNIssxpFN97j63uW4O/JSUksa1o+ezLGY/r4/swsB2dTDG8NKk9bw2eQMvjejEZV39C0qylh944PyW3HhGEyqWieDP9fHc9cViKpcrxYT7+gd8Ee+MDMtlb89mx/4jzHh4gKcbhQNJqfR/bgrdG0fyoZ95VPM2J3DzJwuJrFiasbf2PqUnad7mBG74eAE1K5Xh8YvacH6b2scCpIwMy7rdiUxes5tvFsWwNSGJNnUr8+zlHbIdgrzho/ks3LaPPx8akG2PV1p6Bjd8vIC5mxMYe2uffOVDzdywhxcnrWNJ9H7ATVxIS7fs2H+EcqXCuaxrfTo1qMqYedEs3b4/z6HawpKRYflw1hZenbyBxOQ0GkaWp0KZCNbEHqRSmQheGNGJge3y39OZnmH5Yt42Zm9MYNveJJrXqkj/5jUY1rV+UGeqB4oKaebD49+vYMy8aB48vyV3+2YbbdlzmKFvziKqWjm+vb1vSPVEnE4yZy09d3nHU5ZIySzv8OuKWMb99dQ3Qmstt362iNkb9zD1obNznIGSmJzK49+v5OdlO+nfogYvX9mZGkU0UycvGRmWi16bAcDE+87Mc993pm/ipd/XU6VcKW48owlntaxJZIXSWFxCbaj+nqHuYHIqf3l/nm9ooSoRYYbF0fsY1qU+L43o7Om5klPTeXDcMsaviD1WjDf2YDKt61Rm9HXdg5YyMHODy+ny2gv19IQ1vDd9M7/e099T3bkl0fsYNXo+NSqW5oUrOtG9cSQZGZYv5kfz1PjVRFUrz5hbeuU6Uyw9w/LL8p08N3Ed8YeO8r9hHRiepe2ZxSbzClj2J6Vw6RuzOJKazs93nUGdKv7lS2ZkWF6atJ43p22kUWR5hneLYmC7OjSvVRFjDBvjEnlz6iYmrIwlOTWDquVL8eSQ9lzcsW7IzEoE9/t/syiGhVv3cTA5lb7NqjOkc/18110rKRRA5UN6huWhr129m7Na1qRJjQqMXRBNqfAwfr7rjEJJUJXspWdYrvtwPvO37uW72/uekNCd2Xv4twtactc52U+z3xx/iAtens4V3d1Q3slW7jjAXWMWE703iQcvaMXtZzUL+XXPMgvxTf3b2bnOfnzyl9WMnrmFwR3q8r9hHQo9X6ikS05N5+tFMXw2ZyvlS0dwZosa3HZ2s3yXFFm6fT9fzN1Ghq8Uw01nNAlqorO1lvNfnk65UuH8dFc/vz7g52xK4C8fzOWyrlH5GlZctG0ft3++iLjEo7SuU4mklHSi9ybRv0UNXhrR2e/FcvceTuGuMYuZvSmB6/s25onBbdiWcJghb8yiZZ1KfHVrn2yn9We1blciw96aRYvalfjq1t5+3SRn5sBd0S2K/w5pT7nS2R+Tlp7BpvjD1KlcVn93xYgCqHxKz7C88sd6flq2k20JSQzuUJfHB7cptDW5JGcJh45yyeszSUxO4x8Xt2VIl3pMXLmL+79aSr/mNXLMX8v0n59X8cnsrTxzWUeu6B51rHjdmHnb+N+va4msUJrXRnahZ5PAFJoLtp37j9D3mSnZVqbPNG7Bdh7+djnX923Mvy5pG1J3vxI6Pp+7jb//sJJvb+9Dt0a5v/53H0xm8GszqVIu4pTVCLxISknj49lbmbd5L+VKhTOgdU3PhRjBBSlPT1jL6JlbqFq+FEdTM6hQJpyf7z7D72TziSt3cdvni+jVJJL3r+ue61Dp4uh9jHhnDue1qc3b1+Q8C1OKLwVQAXD4aFqhTnGVvG3fm8Tfvl7GvC17j23r3dTlYOR1x3/gSCp//WwhczfvpUvDqtSuVJYFW/eScDiFs1vV5KURnfOcHRRqhrw5C6zlx7vOOOWxbQmHOe+lP+ndtDofXd8j5JLCJXQkpaTR63+T6dE4MtelajbGHeLGjxcQn3iUH+/qF5B1CgPl1xWx/LkuntIRYVzZo4HnsiM/Lt3Bg+OW0aRGBR68oBXntalFWoYlem8SW/ccJjktg0Vb9/LNohiqVSjN+HvyXwRTQpsCKCmxMjIsv66MZeuew4SFGa7v29jv4ZLM5Mmfl+3kcEo6zWtW5KqeDTizRc2QH7LLTuYsqFmPnnNKL2lmHaIZDw8I2NqPUnK9++cmnp6wNseK+5PX7Ob+r5ZSOiKM96/tXuhLChWGGRvieeL7lUTvTcr28dLhYVzcsS73nNtCKR0lmAIokdPAlj2HGfDCtFOqWW+KP8T5L/2ZZx0ikUxp6RkMe2s2sQeO8PVtfY/l1UUnJDF65mY+mbONtnUr8+6obiU6yTgtPYPfVu1m/e5ESoUbtxxYzQqULx1BzYpllMt0GsgtgNKYlEgJ0aRGBS7vGsUHM7dwOCWdhwa2Ii09g3/+uJKypcJDYsq0FA8R4WE8e3lHhr41iwEvTKNJjQqkpGWwY/8RwgyM6t2IJwa3KfEzkSPCwxjcsS6DCVyRWik5FECJlCDPD+9IrcpleHvaJsYt3E6pcEN6huWfF7ctsgVTpXhqW68yUx48i19XxLJo2z4qlilF05oVuKxrfb8TskVKMg3hiZRAq3Ye4JflsexPSuWvZzZVjoaISD5oCE/kNNOuXpUiW/FeROR0oLnMIiIiIh4pgBIRERHxSAGUiIiIiEcKoEREREQ8UgAlIiIi4pECKBERERGPFECJiIiIeKQASkRERMQjBVAiIiIiHimAEhEREfFIAZSIiIiIRwqgRERERDxSACUiIiLikbHWFt7JjIkHtgX5NDWAPUE+x+lI1zU4dF2DQ9c1OHRdg0PXNTgCcV0bWWtrZvdAoQZQhcEYs9Ba272o21HS6LoGh65rcOi6Boeua3DougZHsK+rhvBEREREPFIAJSIiIuJRSQyg3ivqBpRQuq7BoesaHLquwaHrGhy6rsER1Ota4nKgRERERIKtJPZAiYiIiARV0AMoY0wDY8xUY8xqY8wqY8y9vu2RxphJxpgNvq/VfNtbG2PmGGOOGmP+luV5Whljlmb5d9AYc18O57zQGLPOGLPRGPNolu2jjTHLjDHLjTHfGGMq5nD8U8aY7caYQydtf8D3eyw3xkw2xjQKwCXKlxC7rh8bY7ZkeY7OORzfxBgzz3f8V8aY0r7tZxpjFhtj0owxwwN3lbwLsetqfK/F9caYNcaYe3I4/gvf8SuNMR8aY0plOf413/MuN8Z0DeCl8iTEruu5vtfbUmPMTGNM8xyO72aMWeE7/jVjjPFt7+Rr2wpjzM/GmMoBvFSehNh1Pcd3XVcaYz4xxkTkcHxOr9cqvuu5zPe73BDAS+VJEV3XD40xccaYlSdtv8LXhgxjTI4zynLazxjzl5PakGFyeI8Wj6y1Qf0H1AW6+r6vBKwH2gLPAY/6tj8KPOv7vhbQA3gK+FsOzxkO7MLVZ8jusU1AU6A0sAxo63uscpb9Xso8fzbP0dvX7kMnbR8AlPd9fzvwVbCvXzG5rh8Dw/1o8zjgKt/37wC3+75vDHQEPvXneU6j63qD75qEZZ4rh+e/CDC+f19mua4XARN823sD83RdLb5zt/F9fwfwcQ7PP9933YzvOg7ybV8AnOX7/kbgydP9uuJuxrcDLX37/Re4yePr9fEs7awJ7AVKnw7X1ff4mUBXYOVJ29sArYBpQPdc2pznfkAHYFNRvV5L2r+g90BZa2OttYt93ycCa4D6wBDgE99unwBDffvEWWsXAKm5PO25uBdBdkU5ewIbrbWbrbUpwFjfubDWHgR3Zw6UA7JNALPWzrXWxmazfaq1Nsn341wgKpc2BlUoXVd/+K75OcA32bRtq7V2OZDh7/MFS4hd19uB/1prMzLPlUObf7U+uA/9zNflEOBT30NzgarGmLp5XoQgCLHraoHMXqMqwM6TD/Zdp8q+9wKLC2SH+h5uCUz3fT8JuDyXNgZVCF3X6kCKtXa9b78cr0sur1cLVPK9V1TEBVBpeVyCoCiC64q1djrudz55+xpr7To/2uzPfiNx/2cSAIWaA2WMaQx0AeYBtbMEKbuA2h6e6ircnUt26uPuhDLF+LZltuEj3/laA697OOfJbsLdlRa5ULiuwFPGDRO9bIwpk83x1YH91trMN8STjw85IXBdmwFXGmMWGmMmGGNa5NHeUsAoYKIfz11kQuC63gz8aoyJwV2vZ3I4PiaH41dxPBi7Amjgoc1BU8TXdQ8QkWXoaDh5XJdsXq9v4HpRdgIrgHszbx6KUiFd18JyZQi0ocQotADKuHyjb4H7MnuCMvnuRPyaDmhc3sylwNf5aYe19gagHu6O4sr8PIcx5hqgO/B8fo4PpBC5ro/hAtIeQCTwSD6eI6SEyHUtAyRbV0n3feDDPPZ/C5hurZ2Rj3MVihC5rvcDF1lro4CPcMP5XtwI3GGMWYQb3knJRxsCqqivq+8cVwEvG2PmA4lAeh6Hnfx6HQgsxb0/dwbeKMr8Mij66xpIxpheQJK1dmWeO4tfCiWA8t1pfAt8Ya39zrd5d+Zwgu9rtsMT2RgELLbW7vYd2yBLctxtwA5OvPOJ8m07xlqbjuvGvNwYE57l+P/68bucBzwBXGqtPepnm4MiVK6rr7vb+q7HR7hufowxv/mO/wBIwA0hRZx8fKgJleuKu7vPPP/3uDyxk69rZpv/hcsbeSDLc+X5t1CYQuG6GmNqAp2stfN8278C+mbzPrCDE4fos77e11prL7DWdsPdzW/ydCECLBSuK4C1do61tr+1tiduiHO97zn8fb3eAHzney/ZCGzB3ZgViUK+rvlp30e+43/185BQ6AErUbKdJRFIvvHs0cAaa23WO72fgOtw3efXAT/6+ZQjyfIisNZux92tZJ4vAmhhjGmC+8O+Crja145m1tqNvu8vBdb6gqnO+MEY0wV4F7gwp3yUwhIq19X3WF1rbayvTUOBlb7nGHhSm6fiuvbHemxboQml6wr8gJu4sAU4C98HUjbX9Wbc3fu5Jw15/ATcZYwZC/QCDthscvsKQwhd131AFWNMS1++zvm+Np3yPmDcjKneuKGba/EN+Rtjallr44wxYcDfcRMiikQIXdes16UMrhf6Kd9z+Pt6jcblCc0wxtTGJURv9rPdAVXY1zU/fKMpfvG9VkcA/QtyTjmJDXKWOnAGrptzOa57diluFkZ1YDKwAfgDiPTtXwd3530Q2O/7vrLvsQq4nowqeZzzItyHzSbgCd+2MGAWbmx9JfAFWWblnXT8c77zZvi+/tu3/Q9gd5bf46dgX79Qv66+7VOyXNfPgYo5HN8UlzS6EdeVXca3vYevPYd97Vil62oBqgLjfdd2Dq7nJLvj03zHZrb3n77tBnjT99gKcpnBc5pd12G+67EMN2OpaQ7Hd/e9pjfh8nMyCw/f63ve9bgPUqPrasGlNKwB1uGGvHI6PqfXaz3gd46/l1xzml3XL4FYXCJ6DL5ZjL7XawxwFPf581sOx+e4H3A2MLeormdJ/adK5CIiIiIeqRK5iIiIiEcKoEREREQ8UgAlIiIi4pECKBERERGPFECJiIiIeKQASkRCkjGmqjHmDt/39Ywx3+R1jIhIYVEZAxEJScatQfaLtbZ9UbdFRORkQa9ELiKST88AzYwxS3GFC9tYa9sbY67HVbyvALQAXgBK4xamPYpb526vMaYZrpBoTSAJuMVau7awfwkRKZk0hCcioepRYJO1tjPw0EmPtQcuw1Wxfwq3SGoXXMX2a337vAfcbd2adX/DLV4rIhIQ6oESkeJoqrU2EUg0xhwAfvZtXwF0NMZUBPoCX7tlzQAoU/jNFJGSSgGUiBRHR7N8n5Hl5wzc+1oYsN/XeyUiEnAawhORUJUIVMrPgdbag8AWY8wVAMbpFMjGicjpTQGUiIQka20CMMsYsxJ4Ph9P8RfgJmPMMmAVMCSQ7ROR05vKGIiIiIh4pB4oEREREY8UQImIiIh4pABKRERExCMFUCIiIiIeKYASERER8UgBlIiIiIhHCqBEREREPFIAJSIiIuLR/wMFzUCoo+zjywAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "multi_df.groupby('time').sum()[['V1', 'V2']].plot(figsize=(10, 6))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now it is straightforward to build this forecast using `VARModel` and plot the results as follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Use VAR model to forecast this multivariate time series\n",
    "from kats.models.var import VARModel, VARParams\n",
    "\n",
    "params = VARParams()\n",
    "m = VARModel(multi_ts, params)\n",
    "m.fit()\n",
    "fcst = m.predict(steps=90)\n",
    "\n",
    "m.plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4. Hyperparameter tuning\n",
    "\n",
    "To identify which hyperparameters to use for a specfied forecasting model, we have classes in Kats that allow you to efficiently identify the best hyperparameters.  Here we will provide an exmaple of how to do hyperparameter tuning for an ARIMA model that using the `air_passengers` data set.\n",
    "NOTE: This example requires ax-platform be installed. For example, `pip install ax-platform` or `pip install kats[all]`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import kats.utils.time_series_parameter_tuning as tpt\n",
    "from kats.consts import ModelEnum, SearchMethodEnum, TimeSeriesData\n",
    "from kats.models.arima import ARIMAParams, ARIMAModel\n",
    "\n",
    "from ax.core.parameter import ChoiceParameter, FixedParameter, ParameterType\n",
    "from ax.generators.random.sobol import SobolGenerator\n",
    "from ax.generators.random.uniform import UniformGenerator\n",
    "warnings.simplefilter(action='ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The method we use to hyperparameter-tuning is a static method called `create_search_method`.  To call this method, we need to specify the type of search we are doing and the search space for the parameters.  We specify the search space for the parameters by defining a dictionary for each parameter and combining these dictionaries into a list.  Here we are specifying that we want to look at all ARIMA(p,d,q) models where the values p, d, and q are either 1 or 2."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "parameters_grid_search = [\n",
    "{\n",
    "    \"name\": \"p\",\n",
    "    \"type\": \"choice\",\n",
    "    \"values\": list(range(1, 3)),\n",
    "    \"value_type\": \"int\",\n",
    "    \"is_ordered\": True,\n",
    "},\n",
    "{\n",
    "    \"name\": \"d\",\n",
    "    \"type\": \"choice\",\n",
    "    \"values\": list(range(1, 3)),\n",
    "    \"value_type\": \"int\",\n",
    "    \"is_ordered\": True,\n",
    "},\n",
    "{\n",
    "    \"name\": \"q\",\n",
    "    \"type\": \"choice\",\n",
    "    \"values\": list(range(1, 3)),\n",
    "    \"value_type\": \"int\",\n",
    "    \"is_ordered\": True,\n",
    "},\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we are going to create a grid search with these parameters.  The full list of arguments of the `create_search_method` are as follows:\n",
    "* **Parameters:** List[Dict], this is a list of dictionaries, where each dictionary gives the search space for a parameter      \n",
    "* **selected_search_method:** SearchMethodEnum, the type of search method used to do parameter tuning\n",
    "* **objective_name:** str, the nume of the objective function used for the search (this is arbitrary)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "parameter_tuner_grid = tpt.SearchMethodFactory.create_search_method(\n",
    "    objective_name=\"evaluation_metric\",\n",
    "    parameters=parameters_grid_search,\n",
    "    selected_search_method=SearchMethodEnum.GRID_SEARCH,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have defined our search grid, we need to define the metric we are calculating at each point on the grid.  Given a set of parameters p, q, and d, we define our evaluation function to be mean absolute error (MAE) of the forecast for the test data set (using an 80/20 training-test split) using these respective parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Divide into an 80/20 training-test split\n",
    "split = int(0.8*len(air_passengers_df))\n",
    "\n",
    "train_ts = air_passengers_ts[0:split]\n",
    "test_ts = air_passengers_ts[split:]\n",
    "\n",
    "# Fit an ARIMA model and calculate the MAE for the test data\n",
    "def evaluation_function(params):\n",
    "    arima_params = ARIMAParams(\n",
    "        p = params['p'],\n",
    "        d = params['d'],\n",
    "        q = params['q']\n",
    "    )\n",
    "    model = ARIMAModel(train_ts, arima_params)\n",
    "    model.fit()\n",
    "    model_pred = model.predict(steps=len(test_ts))\n",
    "    error = np.mean(np.abs(model_pred['fcst'].values - test_ts.value.values))\n",
    "    return error"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have our grid and our evaluation functions defined, we can display our evaluation metric for each point on the grid using the following function calls."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>arm_name</th>\n",
       "      <th>metric_name</th>\n",
       "      <th>mean</th>\n",
       "      <th>sem</th>\n",
       "      <th>trial_index</th>\n",
       "      <th>parameters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0_0</td>\n",
       "      <td>evaluation_metric</td>\n",
       "      <td>115.201849</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>{'p': 1, 'd': 1, 'q': 1}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0_1</td>\n",
       "      <td>evaluation_metric</td>\n",
       "      <td>54.991723</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>{'p': 1, 'd': 1, 'q': 2}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0_2</td>\n",
       "      <td>evaluation_metric</td>\n",
       "      <td>183.293937</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>{'p': 1, 'd': 2, 'q': 1}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0_3</td>\n",
       "      <td>evaluation_metric</td>\n",
       "      <td>157.331347</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>{'p': 1, 'd': 2, 'q': 2}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0_4</td>\n",
       "      <td>evaluation_metric</td>\n",
       "      <td>52.021996</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>{'p': 2, 'd': 1, 'q': 1}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0_5</td>\n",
       "      <td>evaluation_metric</td>\n",
       "      <td>56.346372</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>{'p': 2, 'd': 1, 'q': 2}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0_6</td>\n",
       "      <td>evaluation_metric</td>\n",
       "      <td>141.107489</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>{'p': 2, 'd': 2, 'q': 1}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0_7</td>\n",
       "      <td>evaluation_metric</td>\n",
       "      <td>165.195864</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>{'p': 2, 'd': 2, 'q': 2}</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  arm_name        metric_name        mean  sem  trial_index  \\\n",
       "0      0_0  evaluation_metric  115.201849  0.0            0   \n",
       "1      0_1  evaluation_metric   54.991723  0.0            0   \n",
       "2      0_2  evaluation_metric  183.293937  0.0            0   \n",
       "3      0_3  evaluation_metric  157.331347  0.0            0   \n",
       "4      0_4  evaluation_metric   52.021996  0.0            0   \n",
       "5      0_5  evaluation_metric   56.346372  0.0            0   \n",
       "6      0_6  evaluation_metric  141.107489  0.0            0   \n",
       "7      0_7  evaluation_metric  165.195864  0.0            0   \n",
       "\n",
       "                 parameters  \n",
       "0  {'p': 1, 'd': 1, 'q': 1}  \n",
       "1  {'p': 1, 'd': 1, 'q': 2}  \n",
       "2  {'p': 1, 'd': 2, 'q': 1}  \n",
       "3  {'p': 1, 'd': 2, 'q': 2}  \n",
       "4  {'p': 2, 'd': 1, 'q': 1}  \n",
       "5  {'p': 2, 'd': 1, 'q': 2}  \n",
       "6  {'p': 2, 'd': 2, 'q': 1}  \n",
       "7  {'p': 2, 'd': 2, 'q': 2}  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parameter_tuner_grid.generate_evaluate_new_parameter_values(\n",
    "    evaluation_function=evaluation_function\n",
    ")\n",
    "\n",
    "# Retrieve parameter tuning results\n",
    "\n",
    "parameter_tuning_results_grid = (\n",
    "    parameter_tuner_grid.list_parameter_value_scores()\n",
    ")\n",
    "\n",
    "parameter_tuning_results_grid"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the calculations in the table above, we can conclude that ARIMA(2,1,1) has the minimal error of 52.02."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 5. Backtesting\n",
    "\n",
    "Kats provides a backtesting module that makes it easy to to compare and evaluate different forecasting models.  While our hyperparameter tuning module allows you to compare different sets of parameters for a single base forecasting model, backtesting allows you to compare different types of base models (with pre-specified parameters).  \n",
    "\n",
    "Our backtesting module allows you to look at multiple error metrics in a single function call.  Here are the error metrics that are currently supported:\n",
    "* Mean Absolute Error (MAE)\n",
    "* Mean Absolute Percentage Error (MAPE)\n",
    "* Symmetric Mean Absolute Percentage Error (SMAPE)\n",
    "* Mean Squared Error (MSE)\n",
    "* Mean Absolute Scaled Error (MASE)\n",
    "* Root Mean Squared Error (RMSE)\n",
    "\n",
    "Our example below shows how you can use the `BackTesterSimple` class to compare errors between an ARIMA model and a Prophet model using the `air_passengers` data set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from kats.utils.backtesters import BackTesterSimple\n",
    "from kats.models.arima import ARIMAModel, ARIMAParams\n",
    "\n",
    "backtester_errors = {}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, we define a backtester to look at each of the supported error metrics for an ARIMA(2,1,1) model.  We specify in the `BackTesterSimple` definition that we are using a 75/25 training-test split to train and evaluate the metrics for this model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "params = ARIMAParams(p=2, d=1, q=1)\n",
    "ALL_ERRORS = ['mape', 'smape', 'mae', 'mase', 'mse', 'rmse']\n",
    "\n",
    "backtester_arima = BackTesterSimple(\n",
    "    error_methods=ALL_ERRORS,\n",
    "    data=air_passengers_ts,\n",
    "    params=params,\n",
    "    train_percentage=75,\n",
    "    test_percentage=25, \n",
    "    model_class=ARIMAModel)\n",
    "\n",
    "backtester_arima.run_backtest()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After we run the backtester, the `errors` attribute will be a dictionary mapping each error type name to a its corresponding value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "backtester_errors['arima'] = {}\n",
    "for error, value in backtester_arima.errors.items():\n",
    "    backtester_errors['arima'][error] = value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we run another backteseter to caluculate the same error metrics for a Prophet model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this.\n",
      "INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.\n"
     ]
    }
   ],
   "source": [
    "params_prophet = ProphetParams(seasonality_mode='multiplicative') # additive mode gives worse results\n",
    "\n",
    "backtester_prophet = BackTesterSimple(\n",
    "    error_methods=ALL_ERRORS,\n",
    "    data=air_passengers_ts,\n",
    "    params=params_prophet,\n",
    "    train_percentage=75,\n",
    "    test_percentage=25, \n",
    "    model_class=ProphetModel)\n",
    "\n",
    "backtester_prophet.run_backtest()\n",
    "\n",
    "backtester_errors['prophet'] = {}\n",
    "for error, value in backtester_prophet.errors.items():\n",
    "    backtester_errors['prophet'][error] = value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we can compare the error metrics for the two models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>arima</th>\n",
       "      <th>prophet</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mape</th>\n",
       "      <td>0.120354</td>\n",
       "      <td>0.073343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>smape</th>\n",
       "      <td>0.124584</td>\n",
       "      <td>0.069898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mae</th>\n",
       "      <td>54.348743</td>\n",
       "      <td>29.219968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mase</th>\n",
       "      <td>2.674938</td>\n",
       "      <td>1.438149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mse</th>\n",
       "      <td>5052.300405</td>\n",
       "      <td>1103.835150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rmse</th>\n",
       "      <td>71.079536</td>\n",
       "      <td>33.224015</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             arima      prophet\n",
       "mape      0.120354     0.073343\n",
       "smape     0.124584     0.069898\n",
       "mae      54.348743    29.219968\n",
       "mase      2.674938     1.438149\n",
       "mse    5052.300405  1103.835150\n",
       "rmse     71.079536    33.224015"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame.from_dict(backtester_errors)"
   ]
  }
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